Lead Workforce Scientist
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care.
What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you.
Lead Workforce Scientist (P5) | Focus Area: Employee Listening, Culture & Engagement
Senior Individual Contributor | Workforce Intelligence Data Science, Research & Advisory
POSITION SUMMARY
We are seeking an applied workforce scientist who combines advanced quantitative methods, employee listening analytics expertise, and business judgment to reveal how employees experience the organization and what most influences engagement, culture, retention, and organizational health. The role is designed for complex workforce phenomena and strategic uncertainty, not only defined analytical needs. The Lead Workforce Scientist peers around corners, surfacing the risk, opportunity, or question that leaders did not yet know existed and making previously unseen workforce dynamics visible and actionable.
The Lead Workforce Scientist develops advanced models, methodologies, and analytical assets that connect employee voice with workforce, operational, and business outcomes. These capabilities are deliberately built to discover patterns beyond the questions the organization is already asking, expanding what Workforce Intelligence is capable of knowing. The role applies statistical modeling, survey science, natural language processing, and responsible AI to convert structured and unstructured listening signals into enterprise insight and practical recommendations. The ideal candidate is equally energized by the workforce question and the analytical challenge, and can translate complex evidence into clear guidance for senior leaders while protecting employee privacy and trust.
KEY RESPONSIBILITIES
Data Science & Modeling | Analytical Data Development & Reproducibility
- Build and validate statistical and machine learning models, including but not limited to regression, classification, survival analysis, clustering, and key-driver analysis, to explain and predict engagement, retention, culture, and organizational health outcomes.
- Design rigorous analyses, including quasi-experimental and causal inference approaches, to assess the impact of programs, leader actions, and listening interventions.
- Apply survey science and psychometrics, including sampling, weighting,...
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