Data & Analytics

Data & Analytics

Glocomms: A specialist Data & Analytics talent partner

The future of data & analytics is here, and itโ€™s changing the way businesses hire and job seekers find employment. With the right data and analytics tools, businesses can now make informed decisions when it comes to hiring and employee development.

At Glocomms, we specialize in providing top-tier data and analytics talent on a permanent or freelance/contract basis. Our experienced consultants have a deep understanding of the Google Cloud data and analytics industry and can help you find the perfect candidate to meet your specific needs. Whether you're looking for a permanent employee with expertise in data warehousing, data engineering, machine learning, or data analysis, or a freelancer to help with a short-term project, we can help you find the right fit quickly and efficiently.

Glocomms is committed to providing the tools and insights that will help both employers and job seekers. With our data and analytics solutions, businesses can find the best talent for their team and job seekers can find the right career path.โ€‹

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Benefits of working with us

Our Data & Analytics recruitment specialists support growing technology businesses source the right go-to-market strategy talent, manage the recruitment process and facilitate onboarding. With multi-lingual language support, we provide international recruitment expertise to secure business-critical talent across Europe.

Our recruitment benefits

Experience

We have a decadeโ€™s worth ofData & Analyticsexperience as a leading talent partner in Technology.

Network

A vast, global network of the best, in-demandData & Analyticstalent.

Knowledge

Our award-winning talent specialists offer bespoke, tailored guidance on the latest hiring trends.

At Glocomms, we are dedicated to cultivating enduring alliances grounded in trust, honesty, and shared prosperity. Our commitment lies in delivering customized solutions that align with your distinct demands, granting adaptable alternatives to match your Data & Analytics recruitment preferences. Whether you seek swift placement for pivotal roles or aspire for strategic talent acquisition solutions, our arsenal of resources and proficiency ensures successful outcomes. Share your vacancy with us today.

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Data & Analytics Jobs

With the rise of big data and the Internet of Things (IoT), the volume, variety, and velocity of data are set to exponentially increase. At Glocomms, we comprehend these evolving needs and are committed to connecting you with the right Data & Analytics career opportunities.

Azure Data integration Engineer

Azure Data Integration Engineer Contract: 12 Month Extendable Location: REMOTE TO SWITZERLAND (with occasional visits to their site in the North ofSwitzerland) Language: English I am assisting a reputable holding company who is in the search for a Azure Data Integration Engineer to work side by side with the Lead Data integration Engineer on a external basis Currently, they have one Data Integration Engineer handling all BAU (Business As Usual) tasks independently. We need someone to support him as his right-hand person and to ensure continuity in his absence. This role is crucial for maintaining and enhancing our Azure Cloud Infrastructure. Roles and Responsibilities: Integrate all data within our Azure Cloud Infrastructure, ensuring seamless data flow and connectivity. This includes setting up data pipelines, configuring data sources, and ensuring data is accurately ingested into the system. Monitor the data interface on our Azure Cloud Infrastructure, identifying and resolving any issues promptly. This involves setting up alerts, performing regular health checks, and ensuring data availability and reliability. Analyze all data flowing through our Azure Infrastructure to ensure data integrity, accuracy, and performance. This includes performing data validation, identifying anomalies, and optimizing data processing workflows. Participate in any other Azure data-based projects that the company undertakes during this timeframe. This could involve collaborating with other teams, contributing to project planning, and implementing new data solutions to support business objectives. Act as the right-hand person to the lead Data Integration Engineer, providing support and ensuring continuity in his absence. This includes understanding the existing data architecture, maintaining documentation, and being prepared to step in and manage tasks independently when needed. Skills and Qualifications: Strong background in Microsoft Azure, with hands-on experience in integrating Azure data. Experience in monitoring and analyzing data within Azure Cloud Infrastructure. Ability to set up monitoring tools, create dashboards, and generate reports to track data performance. Proficiency in data integration tools and techniques, with a solid understanding of cloud-based data management. Knowledge of scripting and automation tools to streamline data processes. Strong analytical and problem-solving abilities, with a focus on delivering high-quality solutions. Ability to troubleshoot and resolve data-related issues efficiently. Ability to work effectively in a collaborative, fast-paced environment. Strong interpersonal skills and the ability to build positive relationships with team members and stakeholders.

Negotiable
Schweizer-Reneke
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Senior Manager of Privacy Engineering

Senior Manager of Privacy Engineering Orlando, FL We are thrilled to announce an opening for a Senior Manager of Privacy Engineering at a vibrant Orlando, Florida office. This pivotal role is aimed at a seasoned professional who will lead the incorporation of comprehensive privacy measures into our technological innovations, ensuring adherence to 'Privacy by Design' principles. The ideal candidate will possess an advanced degree in software engineering, extensive experience in implementing privacy-enhancing technologies, and a thorough grasp of global data protection regulations. Your responsibilities will include enforcing compliance with stringent international legal frameworks, including but not limited to the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States. You will also engage with cross-functional teams to foster a culture of security-first thinking. Leveraging your expertise in global communications, you will be instrumental in setting and enhancing privacy standards across our digital interfaces. Your strategic input will ensure that our digital strategies are not only compliant but also set benchmarks in data privacy, aligning with ongoing changes in international privacy and security standards. This will involve regular audits and updates to our privacy protocols to stay ahead of the curve. A crucial component of your role will be the continuous refinement of our data management practices. You will oversee the development of cutting-edge methods for handling sensitive data, ensuring utmost integrity and confidentiality. This includes architecting secure data storage solutions, enhancing data encryption methods, and implementing rigorous access controls and audit trails to prevent unauthorized data access and leaks. This role requires not only a profound technical and regulatory acumen but also a visionary leader capable of driving innovation in privacy technologies amidst a rapidly changing digital landscape. If you are looking for a role where you can make a significant impact in the field of privacy engineering, apply today to join our forward-thinking team.

Up to US$115000 per year
Orlando
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Lead Salesforce Data Engineer

Job Title: Salesforce Data Engineering Lead We are seeking a Salesforce Data Engineering Lead to design, implement, and manage data-intensive applications related to Salesforce for the company. This role provides subject matter expertise for our integrated Informatica CC360 Master Data Management solution within Salesforce and works closely with the company's Global Technology (GT) teams to deliver innovative data solutions using a range of technologies. The Salesforce Data Engineering Lead also collaborates with vendors and managed service providers (MSPs) for project development and process optimization, while providing level 3 support for incidents and service requests. You will also mentor level 1 and level 2 associates and MSP teams. Key Responsibilities: General Contributions: Support team, department, and business objectives by conducting detailed quantitative and qualitative analysis of business processes and projects. You may also manage small-scale projects or elements of larger ones. Solve complex business requests and make decisions for non-routine issues with moderate risk, ensuring smooth business operations. Assist senior associates in achieving business results by identifying areas for business process improvement, contributing to operating plan development, and ensuring budget adherence. Show personal awareness of strengths and areas for growth, proactively working to enhance skills and knowledge. Perform additional duties as required. Role-Specific Contributions: Partner with Business Analysts and Architects to understand business requirements for new features or capabilities. Convert business requirements and architectural guidance into technical solution documentation and diagrams to support supplier bids. These documents will outline the technical details for the supplier's development work. Design scalable, high-performance data solutions within the Salesforce ecosystem, ensuring alignment with enterprise data management goals, and applying expertise in data sourcing, integration, governance, and security. Develop and document strategies for data migration and integration, ensuring data accuracy, consistency, and traceability during migration and ongoing operations. Lead the development of reporting and dashboard solutions leveraging Salesforce data, meeting business and GT team requirements. Review supplier bids and proposed work orders, providing guidance on technical designs and solutions. Oversee supplier-developed designs and test plans to ensure compliance with approved specifications and company's application development standards. Collaborate with project management roles to set delivery requirements and oversee project execution. Review supplier work products to ensure they meet design specifications and company's best practices. Provide advanced (Level 3) support during production incidents, resolving outages and sharing knowledge to enable suppliers to handle similar issues independently in the future. Contribute to company's Best Practices Library by enhancing technical standards. Perform other relevant tasks as assigned. Candidate Profile: General Requirements: Professional background with expertise in specific disciplines (e.g., Information Technology, Accounting). A college degree or equivalent work experience is required. Specific Requirements: Education: Bachelor's degree in Information Technology or a related field, or equivalent work experience. Preferred Certifications: Database-related certifications (e.g., Azure Data Engineer, Oracle Database SQL Certified Associate). Master Data Management (MDM) certifications (e.g., Informatica Master Data Management Developer). Relevant Salesforce certifications (e.g., Admin, Platform Developer, Integration Architect). Experience: 5-8 years of experience in developing data solutions using integration and transformation tools such as Informatica IDMC or similar platforms (e.g., Microsoft SSIS). 2+ years of experience supporting Master Data Management processes in a highly integrated environment. Informatica CC360 experience is ideal, but other tools (e.g., IBM Infosphere, SAP MDM) are also relevant. Experience with globally sourced operating models and working with suppliers for application development services. Familiarity with project management tools such as Atlassian Jira. Experience with Salesforce application design, delivery, and extension is desirable. Skills and Attributes: Analytical & Strategic Thinking: Strong analytical skills for troubleshooting and identifying system issues, with a proactive approach to resolving potential future challenges. Technical Expertise: Experience in designing and developing data solutions using Informatica CC360, Salesforce Apex & Flows, Heroku Connect, and similar tools. Ability to support Master Data Management (MDM) processes and leverage SQL for data querying and modification. Experience in enterprise reporting and analytics tools. Proficient in debugging and troubleshooting data-related applications (Splunk experience is a plus). Familiarity with Salesforce data processing, integration, and customization is highly advantageous. Project Management Skills: Ability to gather business requirements, plan, execute, and deliver Salesforce solutions on time and within budget. Interpersonal Skills: Effective communication to explain technical concepts to non-technical stakeholders. Strong customer service focus to understand and meet client needs. Collaborative mindset to work with Global Technology teams, vendors, and MSPs to drive successful project outcomes. Leadership capabilities to inspire and guide teams in the successful implementation of data solutions. Additional Attributes: Adaptability to change within a dynamic, matrixed environment. Curiosity and commitment to continuous learning, staying up-to-date with Salesforce and industry advancements. This role provides an opportunity to play a key part in delivering impactful data solutions that support company's growth and operational excellence.

US$80000 - US$140000 per year + Bonus
Orlando
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Backend Developer

About the Company A leader in the biopharmaceutical industry, our client specializes in cutting-edge predictive digital twin technology to drive innovation in biopharmaceutical process development and manufacturing. By integrating artificial intelligence with biochemical networks, they enhance productivity, product quality, and process robustness. Their solutions support top biopharma companies worldwide in optimizing cell line development, media formulation, and process control-reducing experimental efforts, costs, and time to market. Position: (Senior) Backend Developer We are seeking a skilled (Senior) Software Engineer to join a fast-paced, innovative team. This role involves designing, developing, and deploying scalable software systems critical to the company's mission of delivering advanced biopharma solutions. The successful candidate will take ownership of core platform components, contribute to system architecture decisions, and ensure the development of high-quality, reliable, and secure software products. The role requires close collaboration with cross-functional teams, including data scientists, biopharma experts, and product managers, to create user-friendly and high-performance solutions. Key Responsibilities Full-Stack Development: Develop and maintain backend services, APIs, and user interfaces with a focus on scalability and reliability. Implement and optimize platform features to enhance functionality and performance. System Architecture & Design: Lead discussions on system architecture, ensuring scalability, resilience, and maintainability. Solve complex technical challenges while aligning the system with long-term business goals. Machine Learning Integration: Work closely with ML engineers and data scientists to integrate machine learning models into production systems. Optimize ML-powered features for performance and scalability. Performance Optimization: Identify and resolve performance bottlenecks across the platform. Optimize code and algorithms for efficiency, particularly when handling large datasets. CI/CD & Automation: Maintain CI/CD pipelines to ensure seamless deployment and efficient development workflows. Implement best practices for testing, debugging, and version control. Security & Code Quality: Enforce security best practices, ensuring compliance with industry standards for handling sensitive biopharma data. Maintain clean, high-quality code through reviews and testing. Leadership & Collaboration: Mentor junior and mid-level engineers, fostering a culture of continuous learning. Work closely with product teams to align technical solutions with business needs. Documentation: Maintain detailed documentation for system architecture, codebases, and workflows to ensure knowledge transfer and reproducibility. Technical Expertise Software Development: Proficiency in Python and full-stack development, including front-end, back-end, databases, and API design. Expertise in microservices architecture, RESTful APIs, and version control (Git). MLOps & Machine Learning: Experience with MLOps tools like Flyte and backend frameworks such as FastAPI or Flask. Knowledge of deploying and scaling ML models using TensorFlow, PyTorch, or Jax. Cloud & Infrastructure: Hands-on experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Experience with infrastructure-as-code tools like Terraform. Data & Security: Understanding of data engineering, database design, and security best practices for handling sensitive biopharma data. Soft Skills Strong problem-solving ability to tackle complex technical challenges. Excellent communication skills to collaborate effectively across teams and convey technical concepts to non-technical stakeholders. Leadership and mentorship skills to support junior engineers. Ability to work independently while contributing to broader team objectives. This is an opportunity to play a key role in an innovative, high-impact environment at the forefront of biopharma technology.

Negotiable
Frankfurt (Oder)
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Director of Data

Position: Director of Data As the Director of Data, you will be at the helm of building and leading a new team dedicated to driving customer satisfaction and business growth. Reporting to the VP of Product & Engineering, you will play a key role in shaping innovative product experiences that differentiate us in the competitive landscape. Key Responsibilities: Craft and Lead Data Strategy: Design and implement a forward-thinking data strategy that aligns with company goals and enhances customer value. Team Building and Leadership: Assemble and oversee a high-performance, cross-functional team skilled in data analytics, engineering, science, and domain expertise. Cultivate a culture of collaboration and continuous development. Cross-Functional Collaboration: Work closely with the expanding Go-to-Market (GTM) team to address key data needs that drive top-line revenue. Play a key role in fostering a self-service data environment across the organization. Strengthen Data Capabilities: Develop cutting-edge real-time data solutions that blend award availability and pricing data with customer insights. Lead your team in building smarter, more personalized data models and providing actionable insights. Translate Data into Value: Partner with product, engineering, and other teams to embed loyalty data insights into product offerings, driving customer engagement and contributing to overall revenue growth. Who You Are: You are an experienced and results-driven data leader, adept at building and scaling data functions in rapidly evolving environments. You thrive in uniting data engineering, science, and strategy, and are passionate about leading a team tackling complex challenges in the loyalty space. The following qualifications are ideal for this role: Leadership Experience: Proven success in leading and growing cross-functional teams, including data engineers and data scientists. You excel in developing talent and fostering a collaborative, high-performance environment. Technical Expertise: Strong background in data engineering and science, with the ability to design data systems from scratch. You've led the development of data capabilities from the ground up and are well-versed in real-time data processing and delivery at scale. Strategic Thinker: Demonstrated success in creating and executing data strategies that generate significant business impact. You understand how to link data initiatives with revenue-driving efforts to create both customer value and company growth. Passionate and Curious: Eager to dive into the world of loyalty programs, pricing models, and award availability, and driven to turn these insights into meaningful outcomes that benefit customers.

US$190000 - US$230000 per year + Equity
New York
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Data Scientist/Machine Learning Engineer

We are working with a leading private equity firm based in the Houston, TX area. Are you passionate about leveraging data to drive strategic decisions and optimize portfolio performance? As a Senior Data Scientist, you will play a pivotal role in analyzing large datasets to uncover insights that guide investment strategies and operational improvements. You will collaborate with investment professionals and other stakeholders to deliver actionable recommendations and support data-centric initiatives across our portfolio. Key Responsibilities Data Analysis: Collect, clean, and analyze large datasets from diverse sources to identify trends, patterns, and investment opportunities. End-to-End Machine Learning: Design, develop, and deploy end-to-end machine learning models, from data preprocessing and feature engineering to model training, evaluation, and integration into production systems. Model Development: Develop predictive models and algorithms to assess risks and forecast performance metrics for potential investments. Visualization: Create compelling data visualizations and dashboards to communicate findings effectively to both technical and non-technical stakeholders. Collaboration: Work closely with investment teams to understand their data needs and provide analytical support for deal sourcing, due diligence, and portfolio management. Reporting: Generate regular reports and presentations that summarize key insights, metrics, and recommendations to inform decision-making. Research: Stay updated on industry trends, tools, and methodologies to enhance the firm's analytical capabilities.

Negotiable
Houston
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Director of Engineering - Knowledge Graphs

Our client is a seeking a highly skilled and experienced Director of Engineering with a strong background in Knowledge Graphs and graph technology. This role will be pivotal in driving the development and implementation of advanced graph-based solutions to enhance our digital identity verification and fraud prevention capabilities. Key Responsibilities: Lead and manage a team of engineers focused on developing and optimizing Knowledge Graphs and graph-based technologies. Collaborate with cross-functional teams, including data science, product management, and operations, to design and implement scalable graph solutions. Drive the architecture, design, and development of graph databases and related technologies to support our product offerings. Ensure the reliability, performance, and security of graph-based systems. Stay current with industry trends and advancements in Knowledge Graphs and graph technology, and apply this knowledge to improve our solutions. Mentor and develop engineering talent, fostering a culture of innovation and continuous improvement. Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 10+ years of experience in software engineering, with at least 5 years in a leadership role. Proven expertise in Knowledge Graphs, graph databases (e.g., Neo4j, Amazon Neptune), and graph-based algorithms. Strong understanding of data structures, algorithms, and software design principles. Experience with large-scale data processing and distributed systems. Excellent problem-solving skills and the ability to think critically and strategically. Strong communication and interpersonal skills, with the ability to collaborate effectively with diverse teams. Passion for innovation and staying ahead of industry trends. Preferred Qualifications: Experience in the identity verification or fraud prevention industry. Familiarity with machine learning and AI techniques related to graph technology.

US$250000 - US$325000 per year
United States of America
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Machine Learning Engineer

Machine Learning Engineer Our client is a leading clean power company. Position Overview: Seeking a Machine Learning Engineer specializing in time series data analysis to develop and optimize machine learning solutions for forecasting, anomaly detection, and predictive analytics. Key Responsibilities: Develop and implement machine learning models for time series data. Design scalable data pipelines. Optimize models for performance and scalability. Analyze complex datasets for actionable insights. Stay updated on machine learning advancements. Collaborate with cross-functional teams and mentor team members. Ensure compliance with ethical guidelines and privacy laws. Qualifications: Bachelor's or master's degree in a relevant field. Proficiency in machine learning frameworks (TensorFlow, PyTorch, Keras). Expertise in time series data and programming languages (Python, R). Experience with big data technologies and CI/CD practices. Strong problem-solving and collaboration skills. Preferred Skills: Experience in the solar industry and proficiency with Microsoft Excel. Benefits: Attractive compensation, health and dental insurance, 401k plan, paid cell phone service, employee share plan, company-paid lunch, and gym membership.

US$160000 - US$185000 per year
Stamford
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Machine Learning Engineer

Machine Learning Engineer Our client is a leading clean power company. Position Overview: Seeking a Machine Learning Engineer specializing in time series data analysis to develop and optimize machine learning solutions for forecasting, anomaly detection, and predictive analytics. Key Responsibilities: Develop and implement machine learning models for time series data. Design scalable data pipelines. Optimize models for performance and scalability. Analyze complex datasets for actionable insights. Stay updated on machine learning advancements. Collaborate with cross-functional teams and mentor team members. Ensure compliance with ethical guidelines and privacy laws. Qualifications: Bachelor's or master's degree in a relevant field. Proficiency in machine learning frameworks (TensorFlow, PyTorch, Keras). Expertise in time series data and programming languages (Python, R). Experience with big data technologies and CI/CD practices. Strong problem-solving and collaboration skills. Preferred Skills: Experience in the solar industry and proficiency with Microsoft Excel. Benefits: Attractive compensation, health and dental insurance, 401k plan, paid cell phone service, employee share plan, company-paid lunch, and gym membership.

US$150000 - US$185000 per year
Stamford
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Data Software Engineer

Data Software Engineer Location: Houston, Texas (Hybrid) Company Overview: Our client, is a leader in energy space, and they're backed by a world renowned investment firm Position Summary: Key Responsibilities: Data Pipelines: Design and implement data pipelines for ML and AI models using Azure and Databricks. DataOps/MLOps: Manage routine operations. Domain Expertise: Apply mathematical and statistical knowledge to assess data quality and model insights. Trading Tools: Maintain real-time trading tools for decision-making. Technical Translation: Simplify complex concepts for non-technical stakeholders. Innovation: Research trends in data engineering, AI, and energy storage. Collaboration: Work with engineering, finance, and operations teams. Requirements: Master's in Mathematics, Statistics, Computer Science, or related field. 5+ years in data engineering, ML, and Excel-based workflows with Visual Basic. Proficiency in Python, PySpark, and Visual Basic. Experience with cloud platforms (Azure, Databricks) and big data technologies (Hadoop, Spark). Knowledge of optimization techniques in energy storage.

US$140000 - US$160000 per year
Houston
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Director of Data Governance

Overview: Glocomms is partnered with a major supplier in the US focused on wholesale distribution across a variety of industries with over 100 distribution centers across North America. We are looking for a Director of Data Governance to join this exciting team! This position entails developing and spearheading the strategic direction and requirements for all data domains within the business unit. The role includes offering guidance and leadership in the creation, implementation, maintenance, and enforcement of data standards. Qualifications: Bachelor's Degree in related field with 9+ years of experience and 3+ years in a leadership position Proficiency in crafting and implementing data strategies Knowledge or experience with SAP systems Experience in data governance and standards management Strong program management abilities Background in architecture design or engineering Experience with AI technology is a plus Key Responsibilities: Oversee the governance of data processes and coordinate cross-functional data Direct and manage data changes with thorough control, oversight, approval, communication, and documentation Relay the implications of data changes and work alongside functional and IT leaders to identify the best solutions Implement and follow industry standards and best practices in data governance and management Maintain the integrity and quality of data by conducting regular audits and quality reports Engage in the organization's formal SDLC Process team Responsible for achieving planned results within the organization's policies and guidelines. May manage multiple layers of managers or directly supervise a senior-level staff of professional individual contributors. If you're interested, please apply in directly!

US$150000 - US$200000 per year
Atlanta
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Enterprise Account Executive

About the Role Our platform is designed to help enterprises deploy, manage, and optimize their use of cutting-edge technologies in production environments. By simplifying workflows and offering a customizable, enterprise-grade solution, we enable organizations to adopt modern infrastructure practices without the steep learning curve or operational overhead. This role goes beyond selling - you'll be instrumental in shaping the go-to-market strategy and establishing the processes and team required for long-term growth. Key Responsibilities Sales Execution: Own the entire sales cycle from prospecting to closing, focusing on driving revenue growth through high-value enterprise accounts. Account Strategy: Develop account plans to identify key opportunities and tailor solutions to meet specific customer needs. Market Positioning: Articulate the business and technical value of the platform to diverse stakeholders, from engineers to C-suite executives. Customer Enablement: Collaborate with technical teams to ensure customers successfully implement and maximize the value of the platform. Team Building: As an early member of the sales team, contribute to the development of scalable sales processes and lay the groundwork for future team expansion. Pipeline Growth: Identify and target greenfield opportunities, building relationships with enterprise decision-makers across industries. What We're Looking For Track Record of Success: Consistent overachievement of revenue targets in enterprise software, infrastructure, or DevOps-related sales. Visionary Leadership: Desire to grow into a leadership role, including mentoring junior sales professionals and shaping the future sales team. Technical Acumen: Familiarity with modern infrastructure practices, cloud environments, and the challenges of integrating complex tools in enterprise settings. Consultative Approach: Ability to deeply understand customer challenges and position tailored solutions that drive measurable outcomes. Relationship Building: Proven ability to engage with and influence stakeholders across technical and business functions. Self-Starter: Comfort working in a high-growth, entrepreneurial environment where ambiguity is the norm and initiative is key. Why Join Us? A competitive compensation package with uncapped earning potential. Room for career growth, including opportunities to transition into leadership roles. Equity opportunities in a fast-growing, well-funded startup. A flexible, - hybrid work environment. Access to a forward-thinking team at the forefront of innovation in the software and infrastructure space.

US$150000 - US$200000 per year
New York
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Data & Analytics News & Insights

Demand in Data: Exploring the talent challenges and opportunities in the data & tech industry Image
Highlights

Demand in Data: Exploring the talent challenges and opportunities in the data & tech industry

The global data analytics market is estimated to be valued at $41.5 billion in 2023 and is projected to expand at a CAGR of 30.4% to $345.5 billion by 2028.The data industry has undoubtedly witnessed a remarkable transformation in recent years, driven by the rapid advancement of technologies and an escalating demand for data-driven insights. As this market continues to experience substantial growth, hiring trends are evolving in response to these dynamic changes.ย Our latest report uncovers:Key opportunities and challenges in the data industryThe most in-demand data rolesTechnical, soft, and business skillsets to keep in mind when hiringSalary guides for key data roles in the USA, Asia, UK, and EuropeKey takeaways and recommendations for both hiring managers and professionals

Read More
How to Write a Job Description for a Data Scientist Role Image
data-analytics

How to Write a Job Description for a Data Scientist Role

โ€‹Writing an accurate, concise job description for a Data Scientist role is a vital part of attracting the best candidates for the position, while sharing relevant information about the role on offer. Job descriptions not only assist hiring managers and HR teams to find top talent, but also helps them to compete against other leading employers for the attention of experienced professionals considering new roles. On the other hand, poor job descriptions can have the opposite effect, attracting the wrong or unqualified applicants, or even no applicants at all. When a job description fails to adequately communicate the expectations and requirements of the role, it can lead to a pool of candidates who are unqualified and may discourage qualified professionals from applying too. In this article, we will explore the process of writing a job description for a Data Scientist position that attracts the highest quality candidates.Writing a Data Scientist job description A job description should provide interested candidates with all the information they need to know about a vacant role. The key elements to include in a Data Scientist job description are:The official job title โ€“ With the growth of data teams, itโ€™s important to highlight the specific role youโ€™re looking for, whether thatโ€™s a Data Scientist, Data Analyst or Data Engineer. The purpose of the role and key responsibilities โ€“ Data Scientists are in high demand across a vast range of industries, so what makes this role different? Bear in mind that many experienced professionals are looking for a job with meaning and a purpose that aligns with their values. The objectives of the role โ€“ What do you expect to see from potential candidates in their first month, three months, and in the long term?The experience, skills and qualifications required โ€“ Capture the specific industry experience and business acumen required, as well as soft skills that are crucial to success.The salary โ€“ According to a recent LinkedIn survey, 82% of respondents said seeing a salary range in a job description gives them a more positive impression of a business.The specific compensation structure and benefits on offer, including holiday entitlement โ€“ In a competitive market, offering a strong compensation package is key to secure talent, particularly when hiring for senior Data Scientist positions. The working hours and work location โ€“ If flexible working hours or remote working opportunities are available, this should be outlined clearly. Information about the company.Including this information ensures that your job description attracts positive attention without leaving candidates with unanswered questions about the nature of the role being offered.Main responsibilities of a Data ScientistResponsibilities vary by industry and the size of the data team in question, so accurately defining the responsibilities of an open role assists hiring managers in locating candidates who are best suited to the open position. However, the most common job responsibilities for Data Scientists include:Identifying and utilizing external and internal data sources to enhance business outcomesDesigning tools that improve data mining, data analysis, and validationDesigning and utilizing algorithms and data models to structure data setsDeveloping tools and models of testing that ensure the accuracy of dataPresenting reports of key findings, solutions, and future recommendationsCollaborating with co-workers across departments to maximize productivity and positive outcomesWhen summarizing the main responsibilities within a job description, itโ€™s also important to consider what matters most to potential candidates and highlight the responsibilities and projects that will capture professionalsโ€™ interest. The testimonial below highlights how an accurate and interesting job description can showcase to potential hires the projects they may be involved in and help to attract the right candidates:โ€œI was very interested in the NLP work that Glocomms sent over to me. It is rare to have so much impact on the NLP lifecycle at a large company โ€“ but working for this innovative group allowed me to have that technical roadmap.โ€ - Data ScientistImportant skills and qualifications required for a senior positionSenior Data Scientists are more deeply involved in long-term data driven projects and team management roles.Senior positions often require a bachelorโ€™s degree in data science, statistics, computer science or relevant fields, at least three years of experience in similar roles, and proven abilities in tasks such as preparing unstructured data, leading machine learning and modeling projects, and using SQL and Python for data science applications. Successful candidates also need hard skills like advanced knowledge of data preparation, analysis and cleaning, and experience in using scripting and programming languages like Python, Java, and C++.In addition to technical expertise and experience, soft skills are valuable for Data Scientists, particularly in senior positions. Effective communication, teamwork, and management skills are vital for collaboration across departments, and for managing and mentoring other members of the team. Strong problem solving and critical thinking skills are also vital in a rapidly evolving field like Data Science, so itโ€™s important the job description outlines a blend of both technical hard skills and soft skills. A summary of the company Providing candidates with an overview of the hiring companyโ€™s values, culture and mission is also a crucial part of a Data Scientist job description. Outlining the benefits, the working environment, and why potential candidates should work for the company highlights all the factors that make working there appealing to prospective talent.Hire the best Senior Data Scientists with Glocomms Looking for your next hire? If you need guidance developing a strong job description to attract the right candidates, Glocomms can help. As a leading technology talent acquisition specialist, we can assist you in hiring a skilled Data Scientist with the right skills and experience for the role. Submit a vacancy or request a call back to elevate your hiring process and find the talent you need.

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Empowering Women in Technology: How to Hire More Women in Tech Image
management & culture

Empowering Women in Technology: How to Hire More Women in Tech

โ€‹While women are gaining an ever-strong standing in the Technology workforce, more work is needed to ensure that they enjoy equal opportunity, compensation, and career growth opportunities. According to Deloitte's Women @ Work: A Global Outlook report, while women are becoming better represented in the sector, they still experience non-inclusive behaviors, with 44% of respondents noting that they experienced micro-aggressions or harassment in the workplace in 2023. In this article, we will explore how Tech organizations can empower women, improve their hiring strategies to include more female talent where available, and create a workplace culture that nurtures and supports women in Tech.The importance of diversity in the workplaceDiverse and inclusive workplaces build high-performing teams and motivated, goal-oriented individuals. Todayโ€™s candidates also prioritize and seek out diverse workforces in which they will be accepted, supported, and provided with sufficient growth and development opportunities.Creating a diverse workplace that includes women in the Tech industry will help to create stronger problem-solving approaches and bring new and innovative ideas to your organization.Eliminate unconscious bias in role descriptionsAn important, but often overlooked, factor that contributes to biases in the hiring process is unconscious bias in job titles and role descriptions. Unconscious bias perpetuates assumptions and stereotypes of certain genders, ethnicities, races, ages, and social classes, among other factors. Ensure that you re-frame role descriptions that contain any outdated or gender-biased language to create space for diversity in your hiring process. Use gender neutral pronouns, check your descriptions for biased language, and avoid presenting a โ€˜toxicโ€™ or gender-prejudiced work culture during interviews and communications with applicants.Involve female employees throughout the hiring processWhere possible, introducing your female candidates to current female employees during the hiring and interview processes will assist you in portraying your organization as a diverse and inclusive one. It may also help to improve the hiring experience for female candidates and could help you to attract referrals in the future. Promote family-friendly policiesAccording to Deloitte, women bear the largest responsibility for household tasks. While 88% of the respondents worked full time, almost half of the women polled by Deloitte were also primarily responsible for household tasks such as cooking, cleaning, shopping, or providing care for dependents.Including flexible and family-friendly policies in your hiring process can help to create a more supportive and inclusive work environment for women in the tech industry. Over half of women have noted that working from home has made them more productive, and offering remote working policies could assist your talent in striking a healthier and more sustainable work-life balance while driving your organization forward.Highlight learning and development opportunitiesCareer development is a leading priority for women in tech. Your organizationโ€™s learning and development opportunities and upskilling programs should be highlighted in role descriptions and throughout the hiring process to attract more valuable female candidates.Providing clear pathways for advancement and promoting a culture that values skill development also demonstrates that your company values the career progression and long-term success of its employees. Retaining your workforceOnce you have built a more diverse and inclusive workforce, itโ€™s important to focus on retaining your diverse spectrum of talent. Some of the most significant challenges in retaining talent in the technology industry include a lack of advancement opportunities and a poor work-life balance. To address these concerns, ensure that you provide sufficient career development opportunities and actively promote equal opportunities for advancement into leadership roles for all employees, including women. Additionally, promoting work-life balance through flexible working arrangements and a supportive company culture can help create an environment where current employees feel supported. Find diverse talent with GlocommsGlocomms specializes in assisting technology organizations to secure leading talent for their open roles. Submit a vacancy or request a call back to partner with us and find the right people to support your future in tech.

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data-analytics

How to Switch Industries as a Data Scientist

Data plays an integral part in almost all the technology that we use on a daily basis, whilst also enabling tech professionals to do their jobs. Skilled data professionals have never been in higher demand, and they therefore have the opportunity to work for a wide range of organizations across a variety of sectors, from banking and finance to business and government.For those data scientists looking for a new opportunity and wondering how to switch industries, the answer is almost certainly that itโ€™s much easier than you might think.Why do professionals consider switching industries?40% of the data professionals who participated in our survey are looking for a new career opportunity. Just over a third cited a lack of learning and development as a top factor for wanting to seek new opportunities โ€“ย a much higher proportion than in any other sector that we surveyed. Feeling either unchallenged or bored within their role fell closely behind a lack of learning and development as a reason to look for new opportunities. Quite often, what data scientists want most from their jobs can be found in other industries. Switching roles to work in Financial Services makes sense if you wish to earn a higher salary, for example: senior data scientists earn an impressive average salary of $127,000 in the finance industry. For those wanting to make a difference in society with their data expertise, considering a role in Life Sciences can be a good option, as you have the opportunity to impact whether a new life-saving product reaches the market. As with all of the other sectors included in our Tech Industry Report, higher compensation is the most important deciding factor for data professionals, with most data scientists looking for a 20%+ increase in pay. A desire for higher pay has served as another key reason for professionals across a wide range of industries to leave their jobs and consider switching industries. Flexible working and the option to work from home is very important to almost all of our data respondents. 48% of them said that they would leave their current role or reject a new offer if it were a full-time office role.Define your next stepIf youโ€™re thinking about how to change industries as a data scientist, your first step should be to ask yourself about the type of work that you most enjoy and the various industries that you find particularly interesting and inspiring.Itโ€™s also worth taking the time to research the market conditions of various industries. If there is a particularly high demand for data scientists with your skill set in certain sectors, you may have a strong hand when it comes to negotiating a high salary. A large number of industries benefit immensely from the application of advanced Data Science methodologies, which means that there are plenty of openings for professionals with the required Data Science skills.Utilize your networkOnce youโ€™ve decided on an industry youโ€™d like to work in, itโ€™s time to start reaching out to people with strong experience in that industry. This will give you an understanding of how that sector operates, what the various positions require and the career opportunities that are available to you.Make connections on LinkedIn with people in that industry, and make use of the connections that you already have. They might just be able to provide you with invaluable advice about how to switch career industries and help you land the role that you have in mind.Identify your strengths and core skillsNow is the time to do your natural strengths and hard-earned skills justice. Identify the core skills that could prove valuable to your new employers and ensure that they occupy a prominent position in the CV or resume you submit when applying to jobs. Be sure to have strong examples ready that demonstrate how you have been able to apply these skills in your past positions โ€“ being able to present real-life examples of how you can apply your knowledge can make all the difference when it comes to swaying employers. Make your transferable skills count16% of Britainโ€™s working population can explain precisely how they could transfer their skills to different lines of work. Ensure that you are able to do just that when filing job applications for your next data science role.Do you have exceptional problem-solving skills? Has your capacity for critical or independent thought been praised by your colleagues? If so, you should highlight them in your applications and at interview stage, as these are skills that are transferable to a variety of sectors.Take the next step in your career with GlocommsMake your Data Science career switch today with Glocomms. Glocomms is a leading talent partner specializing in multiple sectors across Technology, Data Science and Cyber Security. View our range of job opportunities across a variety of rapidly-growing industries and register your CV/resume.โ€‹

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data-analytics

Data Science Career Path and Progression

Data Science is critical to the growth of businesses, helping to make key decisions to boost revenue and performance. As a result, the demand for Data Science professionals has seen a rapid increase in recent years, with plenty of room for career growth for those in the industry. Data from LinkedIn suggests Data Science career prospects in the US alone are growing at an annual rate of 35%. This demand is expected to rise in the future, too, making Data Science careers significantly more lucrative. Our own Tech Industry Report highlights that 35% of data professionals are seeking new career opportunities, a figure significantly higher than the other industries surveyed. The findings reveal not only a growing demand for skilled Data Scientists, but also an increasing demand for experienced candidates looking to transition into Data Science.Career paths in Data ScienceIn 2019, it was estimated that 2.7 million new Data Science and Analytics jobs would be created by 2020 in the Asia-Pacific region and that by 2026, the market would generate revenue of $48.0 billion.ย An increasing number of organizations are leveraging Data Analysis to identify new opportunities for growth and operational efficiency. Experienced Data Scientists are in high demand not only in the Technology sectors, but in other major industries such as Pharma, FMCG, Biometrics and many others. ย The Biometrics sector in particular is expected to grow at a CAGR of 15.2% by 2027 as the demand for customer-facing applications and data security increases exponentially. Machine Learning (ML) has developed to become an independent discipline and is predicted to grow from $21.17 billion in 2022 to $209.91 billion by 2029. As a result of this immense growth and the rapid changes in technology, ML professionals are highly sought after. With ever-changing platforms and frameworks, adaptability is key as this market is never stagnant and provides a constant stream of new opportunities.If you are ready to take the next step in your Data Science career, there are many roles and opportunities available. Whether you need to develop new skills or understand how to repurpose your existing skillset, it is worth investing time to research which type role and industry might be most suitable for your experience and career goals. An increasing number of organizations are open to hiring Data Science professionals from other industries as they recognize the current talent pool is small. and candidates might possess transferable skills that are in high demand.Below is a list of the most in-demand Data Science roles:Data ScientistsThis is one of the most in-demand careers currently, with employment in this field is expected to grow by 36% from 2021 to 2031. Data Scientists are needed in just about every sector, from Biotech to Banking, Pharma to Healthcare, and the transferable skills experienced professionals possess means their skillsets are applicable across these sectors. Data EngineersIn 2020, Data Engineering was the fastest growing tech job as these professionals fill an integral role within data-driven organizations. If there is data to process, Data Engineers will be in demand and as data-driven decisions are becoming increasingly relied upon. These skills are also transferable across multiple sectors and industries.Data AnalystsThe U.S. Bureau of Labor Statistics expects that the number of employment opportunities for Data Analysts will grow by 23% between 2021 and 2031. This far exceeds the average 5% growth predicted for other jobs.Data ArchitectsAs businesses focus more on the storing and organization of data, and as data compliance laws become more prevalent, the demand for Data Architects grows exponentially. The BLS predicts that employment of database professionals will increase by 8% from 2020 to 2030.ย Business Intelligence AnalystsBusiness Intelligence (BI) roles have gained prominence in the last five years and the demand for Business Intelligence Analysts has outstripped the supply. The BI market is expected to grow by 11% from 2019 to 2029.Machine Learning EngineersWith the Machine Learning industry experiencing such rapid growth, ML Engineers are always in demand, especially in the Manufacturing sector where career opportunities are vast. Find Data Science career opportunities with GlocommsIf you want to explore a new career path across Data Science, Glocomms have a range of available roles and opportunities that match your experience and skills.As a leading specialist talent partner in Technology, we offer a range of permanent and contract positions to help you define your next career move. Search and apply today. โ€‹โ€‹

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data-analytics

The Evolution of Big Data Recruitment

Discover 5 tips on how big data recruitment can help attract & retain talent. A shortage of talent in data means itโ€™s never been more important for hiring managers and HR to understand how to attract, and just as importantly, retain their talent. According to Agni Ghosh, Vice President of Data at Glocomms USA, while data has always been part of tech, it is now its own beast, and deserves recognition and in turn, creative recruitment strategies to fill the vacant roles that the sector is experiencing in abundance. Here, Agni shares five quick tips on adapting and retaining data talent for businesses and those hiring. Understanding the growth of big data analytics in recruitment Itโ€™s important to recognize just how much of a boom this area of technology has seen. Itโ€™s evolved massively and data skills are now very much sought across a number of industries and sectors that just a few years ago probably hadnโ€™t even heard of a Data Scientist. Because of this, competition for data talent has never been tougher and therefore clients need to get wise to who they are competing with. Itโ€™s also about staying up-to-date with the latest movers and shakers, and trends. Data specialists are seeing growth in new hot areas, such as AI and machine learning, and may make moves into there as opposed to a more traditional medium, so clients need to realize they too need to embrace and adapt to change. Machine Learning used to be part of Data, and has now become its own space in basically 12 months. Therefore, it is really enticing when attracting talent if you are able to say you are looking into machine learning and there may be opportunities to grow this area; this could help align your company to the big data recruitment agencies. Embracing new backgroundsBecause of this talent shortage, thanks to everyone wanting a piece of the data pool, itโ€™s time for employers to look at different, non-traditional backgrounds for their data dream team. Career paths have changed and people are a lot more open to transferring their skills, and thus employers should be too. We have seen emerging biotech firm data specialists head over to financial quant businesses and vice versa, so we all need to wrap our minds around non-traditional CVs and think about what fresh ideas they could bring to the table. Having an open mindset will also help you beat the competition, and when youโ€™re competing with big banks to big tech, itโ€™s important to embrace and evolve to a talent shortage. Attracting talent earlier We really embrace talent as soon as we can at Glocomms, and hiring managers shouldnโ€™t think any differently. Working with a number of colleges and student organizations, itโ€™s important to identify as soon as we know they are a good candidate, and sometimes that means job offers before someone has barely graduated. We have even seen a candidate get a job offer after being discovered via a research paper they produced at college. Remember, if candidates are getting their name out earlier, as a hiring manager, so should you. Motivations and movements Understanding how hot the market is will help to attract talent, but also discovering the real motivations behind wanting a new job will help to foster a positive working relationship. In terms of retention, it could also make the difference between someone staying and someone going. Flexible working policies and the ability to work from home comes up time and time again as the pandemic has indelibly changed the way we work. It has also made in our opinion, candidates a little more up for risk. Life is too short, and they seem so much more open to different career paths and trying something new. Long gone are the days of boomers staying in one company, and while big names used to help get people through the door, the abundance of start-ups with strong financial credentials has also meant hiring managers can no longer rely on names or reputation. Proof points such as evidence of opportunities to progress, as well as regular pay reviews, internal relocation programs, and training is key. Ultimately people stay for the people as well as the business, so ensuring your managers are fully trained to retain talent as well as possible is also crucial. How big data and recruitment can win talent Compensation is a huge driving factor, and weโ€™re seeing 60% plus in terms of inflation compared to last year. Outside of pay, one of the biggest ways to win talent is offering flexible working. We touched on it earlier, but we are advising clients to add it to their benefits package as the new normal. Otherwise, you will lose this talent and you need to stay competitive with the rest of the market. And, not just in terms of home/hybrid working, but also, can you give job seekers the chance to move elsewhere? If you have relocation opportunities, it could make a difference. For example, the pandemic highlighted the need for many to be close to friends and family, so if a company doesnโ€™t need someone in a big city office five days a week, can the role be based in another, smaller hub? Speed is also of the essence. Counteroffers and competing offers are becoming more common, and especially in terms of the older, more traditional clients such as big banks, time is crucial. A start-up without all those HR hoops and tech tests can move in three days flat. People are moving fast and therefore so should businesses. This is one of the areas we spend time educating clients on the most, and we can help facilitate a faster hiring process for you as your talent partner. If you are a start-up yourself, a big attraction is the lure of being part of something new and special. Ownership is exciting, so being able to offer an equity element in your compensation package helps. This is a bit of a cultural shift, but to attract the new generation of talent, weโ€™d recommend such policies. And, while it isnโ€™t always down to money, we have witnessed a $150,000 sign-on bonus before, and we envision it happening again. Especially if you need to buy people out of shares, stocks and equity, it is something to consider. Covering all Data related roles across the various STEM-related markets globally, including Data Science, AI, Machine Learning, Biometrics, Quantitative Analytics and Data Engineering across all markets. Get in touch with one of our consultants to assist with your hiring needs today, or upload a vacancy now.

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