Senior Data Scientist – Supply Chain Operations
About the role
Job Title
Summary
What You’ll Do
- Design and build end-to-end data science solutions to solve complex warehouse problems:
- Labor planning and scheduling optimization
- Productivity and performance analytics
- Wave batching and release optimization
- Flow optimization and congestion reduction
- Predictive maintenance for warehouse automation
- Exception detection and control tower analytics
- Develop models that directly influence operational decisions, including optimization logic and recommendations
- Partner with distribution center operators and SMEs to embed models into workflows
- Apply industrial engineering concepts:
- Capacity planning and constraint analysis
- Workload balancing and throughput optimization
- Queueing and system flow modeling
- Trade-offs between service, cost, and efficiency
- Translate operational problems into mathematical models, simulations, and heuristics
- Extend solutions across supply chain domains (transportation, inventory, customer, quality)
- Build and productionize ML models, optimization engines, simulation frameworks, and pipelines
- Own full model lifecycle: development, testing, deployment, monitoring
- Translate analytics into operational decisions and measurable business outcomes
What You Bring
- Strong hands-on experience building and deploying data science and machine learning solutions
- Deep understanding of warehouse operations and supply chain systems
- Applied industrial engineering mindset with real-world operations experience
- Ability to solve ambiguous business problems end-to-end
- Strong stakeholder engagement and communication skills
- Expertise in Python and SQL
- Experience with platforms like Databricks or Snowflake
- Experience building production-grade pipelines
Minimum Requirements
- Degree or equivalent and typically requires 7+ years of relevant experience
Preferable Skills & Experience
- Simulation, statistical modeling, and optimization (LP/MILP, heuristics)
- Time-series forecasting and machine learning (including anomaly detection)
- Experience designing decision systems (not just predictive models)
- Familiarity with real-time or near real-time decision systems
- Exposure to AI agents or automation
- Supply chain systems knowledge (WMS, LMS, TMS, ERP)
- Experience integrating data across systems
- Strong ability to translate analytics into clear decisions
- Proven ability to influence stakeholders and drive adoption
- Executive-level communication skills
- Direct experience in warehouse/DC problem solving:
- Labor planning
- Flow optimization (slotting, batching, wave release)
- Productivity management
- Automation or equipment analytics
- Exception / control tower analytics
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
McKesson is an Equal Opportunity Employer
Not included in the source posting: about the role, benefits.
Skills
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