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rewarding, and recognizing the individuals who contribute as data scientists. Validating other aspects of the human capital strategy links back to the workforce requirements nested in the workforce plan. The workforce plan should map the competencies required for a data scientist that show how the work contributes to the current processes and products valued by the organization. A solid, logical, and affordable workforce plan is needed to guide the rest of the strategy. The workforce requirements in the workforce plan are the primary retort to those who question the investment in the capability – thus, they must be derived analytically and be defensible in rational discourse. When the organization has an accepted data strategy, the workforce plan and execution can be evaluated to determine if the current data scientist investment supports the new data strategy.
Recruiting the Data Scientist
Given the current and projected shortage of qualified data scientists, we can confidently predict two things related to talent acquisition: the greatest advantage in recruiting data scientists will be the allure of working for public sector institutions, and the greatest challenge will be competing effectively given the much higher total compensation packages from the private sector.
The optimal data scientist recruiting strategy will operate in concert with the workforce plan, the development of the data scientist workforce, and attrition of the workforce. Without a data strategy, the recruiting strategy should aim to keep pace with the capabilities and talent required to perform the current functions.
When a data strategy is published, the recruiting strategy should go beyond keeping pace with today’s requirements and help shape a Big Data workforce that is prepared for tomorrow’s challenges.
In the near term, the recruiting strategy must highlight an employment climate physically and behaviorally that separates one’s own institution from the competition. Important work, leading-edge assignments and great work tools, combine with the draw many public sector organizations have in their mission and purpose.
Part of the data scientist recruiting strategy should include continuing education and a sense of belonging to something much bigger than the candidate could find at another organization. The data scientist recruiting strategy must be supported by the inspiration, development, assignment and retention plans in the data scientist human capital strategy.
The recruiting strategy has to be scalable to adapt to any changes in the workforce plan and any deviations from expected attrition. Our recommendation is to hire at least one year ahead of the known requirement for data scientists until the talent acquisition process is proven.
Predictive hiring is proactive and requires leaders to understand that data scientist recruiting has to differ from many other positions in the organization. Successful recruiting will rely heavily on referrals from inside the community and on long-term recruiting strategies that identify and cultivate a pool of potential data scientists starting as early as high school. Eventually, we expect successful long-term recruiting efforts will require some form of college scholarships with summer internships or significant repayment of college loans in exchange for some years of service.
NEXT ISSUE: PART TWO (Inspiring, Developing, Assigning, Leading and Measuring the Data Scientist). To obtain a certificate in human capital analytics, visit tmgovu.org