Sr. Data Scientist, Ops Research
$136,300–$227,100 year
On-siteIrving, Texas, United States
Job Summary
Architect and implement stochastic process simulation and optimization solutions to enhance supply chain efficiency across inventory, transportation, and labor planning. Develop digital twins and apply frameworks to aid decision-making, translating outputs into concrete recommendations for business partners. Drive adoption of innovative models while measuring their impact on existing systems. Work on strategic in-flight use cases and upcoming projects involving network modeling and transportation optimization. This role sits within the Operations Research group of the Enterprise Data Science Team, applying data science methodologies to interdisciplinary business problems. Candidates must possess 7+ years of experience in probability, statistics, and Python or R to derive business insights that drive innovation at McKesson.
Required Qualifications
- Degree or equivalent
- 7+ years of relevant experience
- Demonstrated experience in developing stochastic process simulations to guide business decisions across inventory, transportation, or other supply chain related fields
- Strong foundation in probability and statistics, including random variables, probability distributions, hypothesis testing, regression, and modern machine learning methods
- Demonstrated experience in data wrangling problems leveraging SQL
- Experience with statistical modeling in Python and/or R
- Experience in communicating results to technical leaders and non-technical executive audiences
- Candidate must be authorized to work in the U.S, now or in the future, without the support from McKesson
Desired Qualifications
- Experience with commercial or open‐source optimization solvers (e.g., CPLEX, Gurobi, Xpress, CBC, GLPK)
- Familiarity with reinforcement learning or approximate dynamic programming techniques
- Experience developing dashboards, applications, or decision‐support tools that expose model outputs to business users
- Exposure to financial modeling, cost optimization, or pricing analytics
- Experience working in modern data and ML platforms such as Databricks, Snowflake, and Azure ML
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