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.

Lakehouse Data Engineer

Our client is a rapidly growing Insuretech company developing innovative products in the insurance industry. We use advanced machine learning to drive optimal claims outcomes. Key Responsibilities: Design and optimize Data Lakehouse architecture for high performance and scalability. Manage data integration from various sources. Collaborate with teams to align data models with business needs. Enforce data governance, quality, and security standards. Automate processes using scripting and CI/CD tools. Troubleshoot and improve system performance. Work with big data tools like Apache Spark and Delta Lake. Maintain Data Lakehouse stability and reliability. Stay updated on big data and cloud technology trends. Skills and Expertise: 5+ years with cloud-based data solutions (Redshift, Snowflake, BigQuery). Experience with AWS Lake Formation. 3+ years in ELT/ETL development. Proficient in Python, Java, or SQL. Strong SQL programming and data modeling skills. Experience with data pipeline and orchestration tools (Hive, Spark, Airflow). Knowledge of containerization (Docker, Kubernetes). Agile development experience. Understanding of machine learning workflows and data visualization tools is a plus. Strong communication and collaboration skills. Nice to Have: AWS certifications. Knowledge of commercial claims management systems.

Negotiable
United States of America
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Lakehouse Data Engineer

Our client is a rapidly growing Insuretech company developing innovative products in the insurance industry. We use advanced machine learning to drive optimal claims outcomes. Key Responsibilities: Design and optimize Data Lakehouse architecture for high performance and scalability. Manage data integration from various sources. Collaborate with teams to align data models with business needs. Enforce data governance, quality, and security standards. Automate processes using scripting and CI/CD tools. Troubleshoot and improve system performance. Work with big data tools like Apache Spark and Delta Lake. Maintain Data Lakehouse stability and reliability. Stay updated on big data and cloud technology trends. Skills and Expertise: 5+ years with cloud-based data solutions (Redshift, Snowflake, BigQuery). Experience with AWS Lake Formation. 3+ years in ELT/ETL development. Proficient in Python, Java, or SQL. Strong SQL programming and data modeling skills. Experience with data pipeline and orchestration tools (Hive, Spark, Airflow). Knowledge of containerization (Docker, Kubernetes). Agile development experience. Understanding of machine learning workflows and data visualization tools is a plus. Strong communication and collaboration skills. Nice to Have: AWS certifications. Knowledge of commercial claims management systems.

Negotiable
United States of America
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Senior PowerBI Developer

We are seeking an experienced Business Intelligence (BI) Developer for a freelance B2B contract role.to join our team and help optimize and enhance our client's data infrastructure. You will play a pivotal role in ensuring scalability, security, and performance while developing innovative BI solutions that empower thousands of users with self-service analytics. Role: BI Developer Location: Krakow Duration: Long Term Hybrid Remote Working Start Date: January Client interviews: This week and week commencing 16th Dec Key Responsibilities: Analyze Data Infrastructure: Review the client's current data systems, identify areas of improvement, and implement optimizations to address scalability, security, and performance challenges. Develop BI Models: Collaborate with stakeholders to design and build robust, user-friendly BI models that support self-service analytics and efficient data consumption. Utilize Modern Tech Stack: Leverage tools such as PowerBI, Azure, Databricks, Python, and Tabular to develop, deploy, and maintain scalable BI solutions. Ensure Data Security: Implement best practices to enhance data security, ensuring compliance with industry standards and safeguarding sensitive information. Optimize Performance: Fine-tune BI systems to improve query performance, reduce latency, and ensure a seamless user experience for thousands of concurrent users. Collaborate Cross-Functionally: Work closely with data engineers, architects, and business teams to understand requirements and deliver tailored solutions. Provide Ongoing Support: Monitor BI systems, address issues proactively, and provide technical support to end-users for continuous improvement.

Negotiable
Krakรณw
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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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Founding Data Engineer

Our client is a fast-growing AI company specializing in the Pharmaceutical Intelligence space. Key Responsibilities: Design, develop, and maintain complex data pipelines that go through multiple stages and transformations. Implement data modeling, normalization, and wrangling of different data formats into a cohesive product. Manage and optimize data storage solutions using technologies such as PostgreSQL, S3/GCS. Orchestrate workflows using tools like Airflow, Prefect, or Dagster. Implement and manage message queues to ensure efficient data processing. Collaborate with cross-functional teams to understand data requirements and deliver solutions that meet business needs. Contribute to the maturation of data infrastructure in a startup environment, from 0 to 1 and beyond. Required Qualifications: Proficiency in Python and experience with PostgreSQL. Hands-on experience with cloud storage solutions such as S3 or GCS. Familiarity with workflow orchestration tools like Airflow, Prefect, or Dagster. Experience with managing message queues. Mid-level or higher experience in managing complex data pipelines. Strong understanding of data modeling, normalization, and data wrangling. Preferred Qualifications: Experience in fast-growing AI-native companies. Proven track record of maturing data infrastructure in startup environments. Ability to handle unstructured and varying data formats effectively. Why Join Us: Be part of an innovative team at the forefront of AI and data engineering. Opportunity to work on challenging projects that make a real impact. Collaborative and dynamic work environment. Competitive salary and benefits package.

US$150000 - US$200000 per year
Brooklyn
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Principal Data Engineer

Seeking a Principal Data Engineer! We're looking for a Principal Data Engineer to lead the data architecture of our SaaS platform. You'll be responsible for driving architecture, making code contributions, and evolving our prototype into a scalable, extensible data platform. Key Duties & Responsibilities: - Set architectural direction for the data systems - Contribute readable, maintainable, and thoroughly tested code - Build prototypes and proofs of concepts - Adhere to software engineering best practices - Collaborate with data engineers and other stakeholders - Mentor and assist other engineers - Improve productivity and velocity across the team Skills & Abilities: - Deep knowledge and experience with modern data infrastructure - Proficiency with various big data technologies - High standards for software engineering - Excellent communication skills - Empathy for others Join us in connecting companies with the communities they operate in to foster mutual success. Apply now!

US$200 - US$220 per year
Brooklyn
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Qlik Developer

We are working with an established Snowflake-Partnered consultancy in search for a Qlik Consultant for a freelance contract role. Role: Qlik Consultant Duration: 3 months extendable Location: Lyon Hybrid Working Start Date: Nov/Dec We are seeking a Qlik Developer responsible for creating and maintaining Qlik Sense dashboards to support Group-level Operations management. The role involves developing dashboards focused on service quality and incoming call metrics to enhance monitoring and reporting. The ideal candidate will work with Qlik Sense and Snowflake to transform data into actionable insights that drive operational efficiency and strategic decision-making. Fluent English and French is a must for this position. If the role is of interest, please apply directly for more information.

Negotiable
Lyon
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PLC Developer

To my Zurich network, I am working with a Swiss consultancy who are urgently searching for a German speaking PLC Developer. Contract duration: 6 months Language: German Speaking Work model: 3 days onsite, 2 days remote Start date: ASAP Client: This consultancy have been in the market for 40+ years, their teams specialise in tech strategy and business innovation, digital solutions and applications, and device and systems engineering. They work with some of the largest companies across the globe, focusing on AI & Data, DevOps, Cybersecurity, Cloud and Applications & Software. Project: Their end customerdevelops and sells machines which are built on a software stack with 3 different programming languages: NC-Code, PLC-Code and .NET. Our client have been supporting the customer for several years on the .NET level, which communicates with the machine hardware over a PLC layer and a NC layer. Currently, the entire software stack is not running as stable as it should, and the main reasons are within the PLC and NC layer. Key initiatives: Analyse existing code (NC and PLC) Debug existing code Rework parts of the existing code Support the conception and architecture approach of a new PLC layer Required Experience: 8+ years' Experience in the following: PLC code development on Siemens PLC NC code development on Siemens Sinumerik ONE Software engineering / conception and architecture PLC development for machine manufacturers To be considered for this role, you MUST be able to speak fluent German (speaking and written)

Swiss Franc600 - Swiss Franc800 per day
Zurich
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Data Domain Lead

Representing an established IT consultancy, we are searching for a Data Lead to join on a freelance B2B contract on a 12 month extendable contract. Role: Data Lead Duration: 12 months (Long Term) Location: Warsaw Hybrid Working Flexibility Start Date: November B2B Freelance Contract Key Responsibilities: Working closely with your manager, you will lead the Data Platform and BI domain You will create standards of delivery and quality, taking into consideration frameworks and best practices Lead the existing data team and collaborate closely on projects Work and communicate closely with customers from a sales perspective Act as the technical referent in solving any issues Profile: Proven experience in delivering data platforms and working as a lead in a team Strong technical experience with experience in modern data platforms, working on Azure and BI environments specifically Good understanding of data architecture in creation and delivery of data platforms and data warehouses Solid leadership experience and great communication skills Fluent English and Polish

โ‚ฌ350 - โ‚ฌ500 per day
Warsaw
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Lead Data Engineer

Representing an established IT consultancy, we are searching for a Data Lead to join on a freelance B2B contract on a 12 month extendable contract. Role: Data Engineer Duration: 12 months (Long Term) Location: Warsaw Hybrid Working Flexibility Start Date: November B2B Freelance Contract Key Responsibilities: Develop and maintain the client's data and reporting platforms Take charge over the full lifecycle of the data platform implementation Provide expertise in Data Warehouse and Lakehouse development for large-scale clients Assist in the technical roadmap and architecture for Data platforms Profile: 5+ years of professional experience as a Data Engineer, working in configuration, deployment and maintenance with Data platforms Strong experience with Azure data services, Databricks and Python SQL scripts Good technical knowledge of CI/CD pipelines and automation practices Pre-sales experience in working with customers and providing solutions Fluent English and Polish

โ‚ฌ250 - โ‚ฌ400 per day
Warsaw
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Azure Data Architect

We are searching for an Azure Data Architect with one of our key clients, focussing on BI and Analytics. Role: Azure Data Architect Location: Lyon Duration: 6 months (Minimum 1 year project) Hybrid Working Start Date: ASAP (November) Role: Collect and understand project requirements Realisation of Proof of Concept Industrialisation of BI Projects and integration of data Work on the migration of BI solutions to Microsoft BI Participate in design workshops Technical monitoring and documentation Technical Context: Proven previous experience as a Data Architect, working specifically only Azure and BI environments Great understanding of data modelling Tools: Databricks on Azure, Power BI for analytics and BI, ADF (Azure Data Factory), as well as Python for specific developments. Proficient with SQL scripts The role involves configuring and managing Databricks clusters, requiring versatile skills across the entire data processing chain. Fluent English To find out more information, please apply directly with an updated CV!

โ‚ฌ500 - โ‚ฌ600 per day
Lyon
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Lead Data Engineer

**Lead Data Engineer Opportunity in Dallas** Base: Up to 165K plus bonus Role Cannot Provide Sponsorship Are you a passionate Lead Data Engineer seeking an exciting new challenge? We're looking for someone with strong coding abilities and substantial experience to join our dynamic team based in the heart of Dallas. This is not just another job; it's a chance to make significant contributions using top-notch technology within the Azure data factory environment. *Role Highlights:* - Permanent, full-time position - Location: On-site at our modern office space in Dallas - Focus on Azure Data Factory technologies The successful candidate will have over 5 years of hands-on experience and demonstrated leadership skills. You'll be responsible for projects that require deep technical knowledge, managing processes efficiently while pushing technological boundaries. *Skills Required:* 1. **Strong Coding Expertise:** - Mastery level required due to the complex nature of tasks. 2. **Azure Knowledge & Experience:** - Proficiency in utilizing Azure services, particularly around data management tools like Azure Data Factory. 3. **Leadership Abilities**: - Proven track record leading teams or projects ensuring smooth execution from conception through delivery. 4. **Data Engineering Acumen**: - Strong experience with ETL pipeline work in addition to understanding migration within ADZ and Copy Data & Data Flow. If you are determined, enjoy solving challenging problems, possess excellent communication skills, thrive when immersed deeply into technicalities but also can see beyond code-this role could provide the perfect next step up your career ladder! Email me at with your most updated CV or to share any referrals for this position!

US$140000 - US$165000 per year
Dallas
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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

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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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