Lead Data Scientist

Lead Data Scientist – Advanced Analytics

You will sit at the intersection of advanced analytics and distribution strategy within a complex, multichannel environment. As the Lead Data Scientist, you own the analytical agenda end to end, from problem framing through executive delivery.

• Define and execute the analytical framework for evaluating agent and channel performance across a multichannel distribution model
• Design and implement predictive models supporting growth opportunity identification, customer experience, retention risk, and channel optimization
• Conduct program evaluation using experimental and quasi‑experimental methods to establish causal impact of business initiatives
• Translate analytical findings into clear, actionable recommendations for senior leadership
• Set and prioritize the analytical agenda independently, focusing on the highest‑value questions
• Operate effectively in a data environment that is not fully controlled or curated, maintaining rigor despite imperfect inputs

• Deliver multiple high‑impact analyses that directly influence distribution strategy, resource allocation, or growth initiatives within the first 6–12 months
• Elevate rigor in causal inference and program evaluation across key business questions
• Become a trusted thought partner to VP and executive stakeholders on analytically complex decisions
• Increase confidence in data‑driven decision‑making in areas with incomplete or ambiguous inputs

• Direct influence on executive decision‑making and business strategy
• High degree of ownership with measurable impact on growth and performance
• Opportunity to define how advanced analytics is applied in a complex, high‑stakes environment
• Visibility that can accelerate career progression

• Master's degree with 4+ years of relevant experience
• 2+ years of project or analytical leadership experience
• Advanced proficiency in Python (pandas, numpy, scikit‑learn, stats models) and SQL
• Strong experience with causal inference, experimental design, or quasi‑experimental methods
• Proven track record working with real‑world, operational data that is incomplete or inconsistent
• Experience structuring analyses in ambiguous environments with evolving data definitions
• Ability to design and execute end‑to‑end analyses, from exploration through modeling and communication
• Ability to operate with minimal supervision and exercise independent judgment
• Demonstrated interest in improving consumer or customer experiences

• PhD
• Experience in healthcare, insurance, or other complex distribution‑driven businesses (helpful but not required)

• Health benefits effective day 1
• Paid time off, holidays, volunteer time, and jury duty pay
• Recognition pay
• 401(k) retirement savings plan with employer match
• Tuition assistance
• Scholarships for eligible dependents
• Parental and caregiver leave
• Employee charity matching program
  
  Network Resource Groups (NRGs)
• Career development opportunities

Base salary range: $142,300 – $195,700 per year, depending on geographic location and individual experience. This role is eligible for a bonus incentive plan.

It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements.

This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.