Senior Data Scientist – Supply Chain Operations
McKesson•Mississauga, ON
•CA$99,100 - CA$132,100•Hybrid
About The Position
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
Requirements
- 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
Nice To Haves
- 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
Responsibilities
- 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
Benefits
- Competitive compensation package
- Annual bonus or long-term incentive opportunities may be offered
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
