HOW TO HIRE A DATA SCIENCE DIRECTOR...  In the middle of nowhere

DISCOVER 

• The hiring issues our client faced

• How perception analysis prevented a culture breakdown

• The future of data science work

• How competitors are leveraging team structure 

   

HOW OUR TALENT RESEARCH UNCOVERED THE HIRING ISSUES OUR CLIENT WAS FACING 

• Location, 36.54%
• Hybrid working, 9.62%
• Nature of role, 13.36%
• Compensation, 3.85%
• Nature of role, 5.78%
• Compensation, 30.77%

 

• Female, 44, 20.95%
• Male, 166, 79.05%

• Our client faced challenges attracting talent due to their office’s remote location, over 100 miles outside London and not situated close to any major towns or cities.
• Given the location and requirement for 5 days a week in the office, London presented an unrealistic talent pool. As such, our mapping sought to identify emerging talent hotspots within a commutable distance from the client’s location, significantly broadening the available talent pool.
• Despite their non-London location, the client held a highly competitive position in terms of both base salary and total compensation: 

• Although a small percentage of candidates received equity benefits from their current employers, the client’s higher bonus structure largely offset the impact of equity on overall compensation, making their offer particularly attractive. 

PERCEPTION ANALYSIS ENABLED OUR CLIENT TO RESOLVE INTERNAL CHALLENGES AND MAINTAIN A POSITIVE BRAND REPUTATION 

Our research revealed that our client’s brand is reputable and well recognised in the market. However, the data science talent pool highlighted areas that required attention: 

• Hybrid working model: Candidates questioned the flexibility and robustness of the hybrid setup and directly compared this to their current setup, with the majority having significantly more flexibility with their work schedule. Conversations highlighted that if our client were to reconsider its hybrid working arrangements, they would then have access to the London talent pool.
• Cultural challenges: A small number of candidates had heard that the culture was highly political which resulted in significant challenges in ‘getting things done’. This reportedly left several employees feeling sidelined and not having a voice in the company. 

 

• Negative Perception, 3%
• Neutral Perception, 8%
• Positive Perception, 89%

WHAT THE MARKET WAS SHOWING OUR CLIENT ABOUT THE FUTURE OF WORK 

• Downsizing teams: Across the market data science teams were being thinned out, particularly in Big Tech and other multinationals. This was largely a reaction to previously overinflated data science teams.
• Integrating teams: The market was moving towards larger teams of machine learning and AI professionals that can operate at higher capacities. Alongside this, moving away from data segregated teams and instead towards developing team that have full-stack capabilities across algorithms and applied data.
• Flexible structure and closer alignment with business goals: Senior sources felt the key to success was ensuring that the data function and wider business avoided a myopic view of data. The data function should operate flexibly across the business, working with each department to achieve specific goals. Some referenced previous success in implementing ‘experimental’ team structures, which enabled the business to assess the best ways to use data to develop new products. 

HOW INTELLIGENCE ON TEAM STRUCTURES ENABLED OUR CLIENT TO EVALUATE THEIR OWN AGAINST KEY COMPETITORS