Senior Data Scientist – Supply Chain Operations

Job Title

Senior Data Scientist – Supply Chain Operations (Warehousing Focus)

Summary

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

What You’ll Do

• Design and build end-to-end data science solutions to solve complex warehouse problems:

  Labor planning and scheduling optimizationProductivity and performance analyticsWave batching and release optimizationFlow optimization and congestion reductionPredictive maintenance for warehouse automationException 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 analysisWorkload balancing and throughput optimizationQueueing and system flow modelingTrade-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 planningFlow optimization (slotting, batching, wave release)Productivity managementAutomation or equipment analyticsException / 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

Our Base Pay Range for this position

$99,100 - $132,100

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McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.

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