Job Description

Salary: $89,700 - 149,500 per year Requirements:

• Were seeking someone with a degree or equivalent experience, along with typically 7+ years of relevant background.
• We need 7+ years of hands-on data science experience, including delivering models to production with measurable business impact, plus 4+ years leading projects or small teams as a technical lead.
• Experience across at least two relevant domains is important, such as pricing, contracting, demand forecasting, supply chain optimization, commercial analytics, or patient/customer experience.
• We value proven success working in cross-functional product and engineering environments.
• Were looking for a bachelors degree in math, statistics, engineering, or another STEM field, or equivalent practical experience.
• Strong knowledge of supervised and unsupervised learning, time series, causal methods/experimentation, and optimization is required; familiarity with LLMs, NLP, and retrieval-augmented workflows is preferred.
• We need advanced skills in Python and SQL, plus proficiency with PySpark and experience with Azure ML, MLflow, model registries, monitoring/telemetry tools such as Evidently, and CI/CD.
• Experience with Git, testing, packaging, pipelines, containerization, cloud performance and cost tuning, observability, and on-call patterns for ML services is important.
• Familiarity with feature engineering and healthcare or commercial datasets is expected.
• We require demonstrated adherence to enterprise cybersecurity standards and secure development practices for data and machine learning.
• Strong executive storytelling skills and the ability to translate technical findings into business decisions and outcomes are essential.

• We identify opportunities to use company data to build innovative, scalable machine learning solutions for complex business problems.
• We develop and implement strategies that improve operational efficiency, automate decision-making, enhance customer outcomes, and optimize resource use.
• We apply advanced analytics to assess organizational performance, simulate the impact of strategic changes, and support use cases such as predictive modeling, forecasting, classification, recommendation systems, anomaly detection, and NLP/LLM.
• We design and build custom machine learning models and algorithms tailored to business needs, then apply them to large datasets to generate actionable insights.
• We partner with cross-functional teams to deploy, monitor, and maintain ML models in production while ensuring scalability, reliability, and enterprise compliance.
• We build and sustain scalable data infrastructure that supports both real-time and batch decisioning, using cloud-native tools and platforms to improve performance and cost efficiency.
• We work closely with business stakeholders to turn requirements into technical solutions and provide strategic guidance on analytics and data direction.
• We ensure strong model governance, documentation, and performance benchmarking while maintaining Responsible AI and data privacy standards.
• We maintain scalable data systems and infrastructure that help our business teams make better decisions.

• AI
• Azure
• CI/CD
• Cloud
• Git
• Support
• LLM
• Machine Learning
• Python
• PySpark
• SQL

More:

We are McKesson, an impact-driven Fortune 10 healthcare company that delivers insights, products, and services to make quality care more accessible and affordable. We foster a culture where people can grow, make an impact, and bring new ideas as we shape the future of health for patients, communities, and our teams. This Senior Data Scientist role is hybrid in Mississauga, Ontario. We offer a competitive Total Rewards package, with base pay for this position ranging from $89,700 to $149,500, and additional compensation such as bonus or long-term incentives may be available. We are an equal opportunity employer and welcome applicants with disabilities, with accommodations available during the hiring process.

last updated 25 week of 2026

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