Glocomms: A specialist Data & Analytics talent partner
The future of data & analytics is here, and it’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.
If you're a Data & Analytics professional, please register your resume.
If you're looking for Data & Analytics talent, please register your vacancy today.
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
We have a decade’s worth ofData & Analyticsexperience as a leading talent partner in Technology.
A vast, global network of the best, in-demandData & Analyticstalent.
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 Science Manager
Position Overview: A global technology business is seeking a highly skilled and experienced Manager of Data Science to join their dynamic team. The ideal candidate will have a strong background in search and recommendation systems. As a Data Science Manager, you will play a pivotal role in leveraging data-driven insights to enhance user experiences, optimize business processes, and drive strategic decision-making across our global platform. You will be a hands-on technical leader while scaling this growing team. Bonus points for experience in ecommerce, retail, marketplaces, or a related field. Qualifications: Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field; advanced degree (e.g., MS, PhD) preferred. Proven track record of 5+ years of experience in data science, machine learning, or related roles, with a focus on ecommerce, marketplaces, or similar domains. Strong proficiency in programming languages such as Python or R, as well as experience with data manipulation, analysis, and visualization libraries (e.g., pandas, NumPy). Demonstrated expertise in designing, implementing, and optimizing search and recommendation algorithms, leveraging techniques such as collaborative filtering, content-based filtering, and deep learning. Experience with big data technologies (e.g., Hadoop, Spark, Hive) and distributed computing frameworks for processing and analyzing large-scale data sets. Excellent communication and interpersonal skills, with the ability to effectively communicate complex technical concepts to non-technical stakeholders and influence decision-making at all levels of the organization. Strong leadership qualities, with a proven ability to inspire and motivate teams, drive results, and foster a culture of excellence and innovation. Passion for leveraging data science and analytics to drive business impact and solve real-world problems in a fast-paced, dynamic environment.
Director of Data Science
A private equity firm with an emphasis on utilizing data science and analytics is seeking a Director of Data Science to directly support their PortCos and help define the growth of the larger Data program. Responsibilities: In this role, you will act as a hands-on technical contributor responsible for working directly with portfolio companies to optimize operations through data analysis and strategic consulting, as well as assisting in alpha generation/daily operations of the larger firm. Additionally, you will help lead a small team in defining and achieving technical goals as the firm continues to grow. Qualifications: Master's degree or higher 4+ years of prior full-time work experience Familiarity working (to some extent) with data science, data analysis, data engineering, and machine learning processes Business strategy/operations research oriented mind-set Prior consulting experience is preferred by not required If you are interested in breaking into private equity and being a key contributor at a dynamic firm - please apply today!
Cloud Security & Infrastructure Engineer
I' m currently partnered with an exciting generative AI-powered research and data platform to bring on a Cloud Security & Infrastructure Engineer to their security team. This client is at the forefront of cutting edge developments in AI to provide new platforms for search, analysis and knowledge discovery. This is an amazing opportunity to play a pivotal role in deploying their AI stack on-prem and collaborating with client and development teams to make critical decisions regarding infrastructure and architecture. Your role will be instrumental in ensuring SOC2 compliance and scaling their solutions while working on the front lines with AI and financial data processing. This is an on site opportunity based in NYC with the potential for hybrid work. Compensation ranges from 120K - 160K Base + Equity. Qualifications: 6 + years of experience working as a cloud architect or similar role. Expertise with AWS or Azure Strong knowledge of cloud security concepts such as authentication/authorization using OAuth, and managing JWT tokens Expertise with Terraform or alternate infra as code languages Expertise with SOC2 or HIPAA Expertise with Python and Bash to automate work flows. Expertise with Kubernetes Ability to communicate effectively with technical and non technical stakeholders. If you enjoy a technical role where you are able to get your hands dirty and have immense impact, this could be the opportunity for you!
Job Title: Product Manager Position Overview: As the Product Manager for CRM, you will play a pivotal role in defining the roadmap and strategy for our CRM platform. You will collaborate closely with cross-functional teams, including engineering, design, marketing, and sales, to ensure that our CRM product aligns with the company's overall objectives and delivers exceptional value to our customers. Key Responsibilities: Lead the strategic development and optimization of our CRM system to ensure seamless interactions and enhance user engagement on a global scale. Drive the evolution of our customer service platform, creating user-centric solutions that redefine industry standards and enhance user satisfaction. Work collaboratively with cross-functional teams across the globe, adapting strategies to diverse markets, and ensuring a unified and exceptional customer experience. Utilize analytics and user feedback to inform product enhancements, maintaining our position at the forefront of technological advancements. Qualifications: Demonstrated success as a Product Manager with a focus on managing CRM systems and evolving customer service platforms. 4+ years as a product manager, relevant experience in customer service filed In-depth knowledge of CRM technologies and a keen interest in staying ahead of trends in the customer service tech landscape. Ability to navigate and excel in a globally dispersed and culturally diverse work environment. E-commerce experience is a plus Perks: Contribute to groundbreaking advancements in social media technology, influencing the way the world connects and communicates. Enjoy a competitive salary along with a comprehensive benefits package.
Principal Machine Learning Engineer
Come join a revolutionary Mental Health startup we're partnering closely with, who's primary focus in 2024 is capitalizing on the explosive development of cutting-edge Ai technology this past year! They're looking to bring on a Principal Machine Learning Engineer who specializes in breaking ground in new markets by applying state-of-the-art technologies, and who's interested in having a direct impact on consumers. What's the Role Really Look Like? Leading new ML initiatives dedicated to supporting the recommendation of various patients to relevant professionals within our network, defining its mission, goals, and strategy. Develop and execute a strategic roadmap for ML and AI applications, aligning technology goals with the company's mission. Define key milestones, timelines, and success metrics to track progress effectively. Bring a broad awareness of the landscape of ML and AI-based tools for solving common end-user problems (e.g. recommendation systems, prediction, generative AI) and taking active steps to provide solutions. Partner with a cross-functional team of data scientists, software engineers, product managers, and designers to deliver AI powered products that will have a direct impact on the well-being of our users. Who Are You? Knowledgeable: You have intimate knowledge of machine learning fundamentals, modeling techniques, productionizing machine learning models, and modern machine learning tool stacks People First: You love the process of analyzing and creating, but also share our passion to help people in need. You know at the end of the day, it's about making the right decisions to provide the best care to our patients. Solution-Oriented: Hands-on expertise in designing, training, fine-tuning hyperparameters, evaluating ML models, and deploying them effectively, leading from the front. Open-Minded: A commitment to staying updated with industry trends and emerging technologies, in addition to being able to always be open to opportunities and new ideas.
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. 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
How to Write a Job Description for a Data Scientist Role
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 – With the growth of data teams, it’s important to highlight the specific role you’re looking for, whether that’s a Data Scientist, Data Analyst or Data Engineer. The purpose of the role and key responsibilities – 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 – 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 – Capture the specific industry experience and business acumen required, as well as soft skills that are crucial to success.The salary – 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 – 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 – 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, it’s also important to consider what matters most to potential candidates and highlight the responsibilities and projects that will capture professionals’ 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:“I 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 – but working for this innovative group allowed me to have that technical roadmap.” - 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 bachelor’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 it’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 company’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.
Empowering Women in Technology: How to Hire More Women in Tech
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. Today’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 ‘toxic’ 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 organization’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, it’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.
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 it’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 – 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 you’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.It’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 you’ve decided on an industry you’d like to work in, it’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 – 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 Britain’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.
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. 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. 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. 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.
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 it’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 It’s important to recognize just how much of a boom this area of technology has seen. It’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 hadn’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. It’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, it’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 you’re competing with big banks to big tech, it’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 shouldn’t think any differently. Working with a number of colleges and student organizations, it’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 we’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 doesn’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, we’d recommend such policies. And, while it isn’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.