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Lead Workforce Scientist (P5) | Focus Area: Strategic Workforce Planning & Organizational Effectiveness
Senior Individual Contributor | Workforce Intelligence Data Science, Research & Advisory
POSITION SUMMARY
We are seeking an applied workforce scientist who combines advanced quantitative methods, workforce planning expertise, and business acumen to help leaders understand how strategy, technology, and operating-model choices will shape future workforce needs. The role is designed for complex workforce phenomena and strategic uncertainty, not only defined planning needs. The Lead Workforce Scientist peers around corners, surfacing the risk, opportunity, or question that leaders did not yet know existed and revealing workforce implications before they become visible through standard planning processes.
The Lead Workforce Scientist develops advanced forecasting, scenario, simulation, predictive models, and analytical methodologies that translate business strategy into quantified workforce choices and organizational recommendations. These capabilities are deliberately built to test uncertainty, detect risks and opportunities the organization was not explicitly looking for, and expand what Workforce Intelligence is capable of knowing about the future. The role integrates HR, financial, operational, and external labor-market evidence to evaluate alternative futures, including how AI and automation may reshape work, skills, roles, and organization structures. The ideal candidate is equally energized by the workforce problem and the analytical challenge, and can turn complex model outputs into clear decisions on workforce investment, organization design, and transformation.
Forecasting, Scenario & Predictive Modeling | Analytical Data Development & Reproducibility
- Build workforce demand and supply forecasting models using, but not limited to, time-series, regression, and machine learning methods that link headcount, skills, capacity, and cost to business drivers.
- Develop scenario and simulation models, such as Monte Carlo, Markov, and stock-and-flow approaches, to test strategic uncertainty, expose hidden dependencies, and quantify future workforce needs under alternative business strategies.
- Build and validate predictive models for talent flows, capacity, capability gaps, and other workforce outcomes, assessing accuracy, stability, and fairness.
- Apply statistical and causal methods to organizational effectiveness questions such as spans and layers, operating models, productivity, and capacity.
- Use Python or R and SQL to integrate and analyze HRIS, finance, operational, skills, and external labor-market data at enterprise scale.
- Develop fit-for-purpose analytical datasets and derived measures that support forecasting, simulations, organization analysis, and workforce decisions.
- Work in cloud data platforms such as Databricks, using version control, documentation, and reproducible methods so analyses and models can be reviewed, reused, and maintained.
- Partner with HR data platform, finance, and technology teams to define data requirements, quality expectations, and sustainable access for workforce planning analyses.
AI & Future of Work Modeling | Domain Leadership & Advisory
- Quantify the workforce implications of AI, automation, and emerging technologies by modeling task-level exposure and potential changes across roles, skills, capacity, and cost.
- Develop scenarios that distinguish human, automated, and AI-augmented work and clarify the choices, assumptions, and uncertainties within each scenario.
- Evaluate external evidence and labor-market signals to inform assumptions about future skills, talent availability, and workforce transformation.
- Partner with technology and product teams to advance AI-enabled forecasting and decision support while applying responsible AI standards.
- Serve as an enterprise subject-matter leader for strategic workforce planning, future of work, workforce intelligence, and organizational effectiveness analytics, helping shape the modeling agenda.
- Peer around corners by detecting signals, structural shifts, and emerging workforce risks or opportunities before they appear in business plans; surface the question or implication leaders do not yet know to examine.
- Translate model outputs into executive-ready choices and recommendations on workforce investments, organization design, and transformation for HR, strategy, finance, and business leaders.
- Operate with significant autonomy as a hands-on senior individual contributor, shaping decisions through expertise, influence, and trusted advisory relationships.
REQUIRED QUALIFICATIONS
- Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Operations Research, or a related quantitative field; master's degree or PhD preferred.
- 8+ years of hands-on experience applying data science, forecasting, simulation, or advanced analytics to workforce planning, workforce intelligence, operations, or business strategy questions.
- Advanced proficiency in Python or R and SQL, including forecasting, simulation, and machine learning libraries, with demonstrated experience developing and validating models end to end.
- Experience working with relational databases and cloud data platforms such as Databricks, Snowflake, or Azure, including creating analysis-ready datasets from imperfect source data.
- Working knowledge of strategic workforce planning methods, organization design principles, labor-market data, and AI-enabled workforce transformation.
- Ability to communicate technical findings to senior, non-technical leaders and translate evidence into actionable recommendations.
SCOPE & IMPACT
- Leads enterprise-wide workforce and organization modeling initiatives with significant strategic impact.
- Defines new forecasting and planning questions, methodologies, and AI-enabled use cases that reveal risks, opportunities, and strategic choices beyond known business requests.
- Influences workforce, talent, organization, and investment decisions across multiple business units through evidence and trusted advisory.
- Creates reusable analytical methods, code, and models that expand what Workforce Intelligence and HR are capable of discovering and knowing.
We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here.
Our Base Pay Range for this position
$122,100 - $162,800
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McKesson is an Equal Opportunity Employer
McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.
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