The demand for data, analytics and insights talent continues to grow rapidly, but hiring remains a major challenge for most companies. As we enter November, here are some of the key issues, challenges and opportunities that we at MBN continue to observe in the data talent domain:
- There is still a significant shortage of qualified talent to fill available data and analytics roles. We believe that job postings in this field have increased over 20% compared to last year, but the supply of talent has not kept pace. Many companies are struggling to find data scientists, data engineers and other roles requiring both technical and business/communications skills.
The supply-demand imbalance gives candidates more leverage and choice, while companies must get creative with hiring, training and retention strategies.
- While demand continues to grow, candidates often lack key skills for analytics and data science roles. Technical skills like Python, R, SQL and cloud platforms are in high demand but, bizarrely, short supply. Soft skills like communication, presentation and ability to translate analytics into actionable business insights are also lacking in many candidates.
Companies are widening talent pools and boosting training/development to help bridge the skills gap.
- Location remains less important for data and analytics roles, with remote work options expanding talent pools. Many companies have embraced remote data teams, as analytics work can often be done from anywhere with the right tools, security and collaboration. However, some positions still require on-site work, and striking the right remote-office balance remains a challenge.
Companies flexible on location may have a hiring advantage and are finding candidates form a much larger talent pool.
- Salaries have risen across data and analytics roles, with senior and specialist positions seeing large premiums. Exceptional talent is commanding higher pay, sign-on bonuses and benefits like stock options. Job-hopping has also increased as candidates jump for higher pay and advancement opportunities with less regard to tenure than we have previously experienced. Retention becomes more important, as it's difficult and expensive to replace departing analysts and data scientists.
Competitive compensation and career growth opportunities are key.
- Despite increased focus on diversity, data and analytics teams remain predominantly male. Women still make up less than 30% of the workforce in this field. Racial diversity is also lagging. Issues range from lack of equal access to STEM education and bias in hiring/promotion to lack of inclusive company cultures.
Data and analytics leaders must prioritise diversity, equity and inclusion efforts from the top-down to drive necessary changes.
- Some data analysts and scientists are choosing to leave the workforce entirely amid "The Great Resignation" trends! Burnout and lack of advancement lead some to “boomerang” back after a break. Flexible arrangements, career coaching and sabbaticals can help companies hold onto valued talent thinking of leaving the field. Strong DEI and company culture are also critical retention tools.
Purpose driven businesses are faring better here though at present there is still much to do to show the link between purpose and retention in the data talent space.
So, plenty of issues evolving and some that appear to be impacting availability of talent in this important domain… so what’s our advice to you?
Advice for Companies Hiring:
- Get creative with hiring tactics, including partnerships with universities/bootcamps and remote talent pools – find the right hiring partner!
- Focus on identifying transferable skills from adjacent fields like social sciences, physics and engineering.
- Develop internal mentorships and training programs to upskill existing employees into data roles.
- Highlight opportunities for career advancement, learning and leadership development.
- Offer competitive pay, flexibility and benefits to attract and retain top talent.
- Prioritise diversity, equity and inclusion efforts to expand talent pipelines long-term.
Advice for Candidates:
- Continue building technical skills and data fluency, even outside formal roles. Pursue online courses, certificates, self-learning projects etc.
- Develop versatility - don't niche down too fast. Experience with a breadth of data tools opens more options.
- Enhance soft skills like communication, collaboration and business acumen - critical for impact.
- Be open to non-traditional backgrounds. Transferable skills are highly valued alongside analytics experience.
- Evaluate corporate culture and EDI commitment before joining a company. Seek supportive learning environments.
- Manage career momentum. Job-hop carefully and strategically once you have a solid base of experience.
We believe that the data analytics talent marketplace remains extremely competitive, but opportunities abound for both employers and job seekers focused on developing skills, expanding talent pools and nurturing supportive, inclusive work cultures. Continuous learning, flexibility and strategic career planning will be keys to success in this fast-changing field. What to know more about how we can help? Reach out to us here.