McKesson Medication Management

Senior Data Scientist - Supply Chain Operations (Warehousing Focus)

McKesson is accelerating a multi-year Supply Chain Operations modernization agenda, starting with near-term value delivery and scaling toward advanced capabilities such as control towers, digital twins, and agent-enabled decisioning.
We are seeking a highly hands-on Senior Data Scientist who combines strong data science expertise with applied industrial engineering experience to solve complex warehouse and distribution center challenges using data and AI.

Note: This position is 2x per week on site in Missassauga following our flex and connect model

• 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

• 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

• Degree or equivalent and typically requires 7+ years of relevant 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