Senior Lead Data Scientist - Health ML & Impact

McKesson Corporation; Irving (TX); On-site; USD 140,000 - 210,000; Full time

Job summary

McKesson Corporation in Irving, TX is seeking a Senior Lead Data Scientist to own the full lifecycle of advanced analytics and ML solutions, from problem framing to production deployment. You will partner with business stakeholders to translate requirements into technical solutions and drive measurable outcomes.

The role requires deep expertise in Python/SQL, time-series/ML methods, and governance across product, engineering, and analytics teams, with a focus on enterprise data platforms and

Qualifications

• 8+ years of hands-on data science experience delivering models to production with measurable impact.
• Proven ability to lead projects or small teams as a tech lead.

Responsibilities

• Identify opportunities to leverage company data to drive ML solutions for business challenges.
• Develop custom ML models tailored to business needs and apply to large datasets.
• Collaborate with cross-functional teams to deploy, monitor, and maintain ML models in production.
• Build and maintain scalable data infrastructure for real‑time and batch decisioning.
• Engage with stakeholders to translate requirements into technical solutions.
• Ensure model governance and performance benchmarking; maintain Responsible AI standards.
• Build scalable data systems and infrastructure to empower business teams.

Skills

Python

SQL

Data storytelling

Executive communication

Education

Bachelor's in STEM or related

8+ years data science experience

Tools

PySpark

Azure ML

MLflow

CI/CD

Job description

McKesson Corporation in Irving, TX is seeking a Senior Lead Data Scientist to own the full lifecycle of advanced analytics and ML solutions, from problem framing to production deployment. You will partner with business stakeholders to translate requirements into technical solutions and drive measurable outcomes.

The role requires deep expertise in Python/SQL, time-series/ML methods, and governance across product, engineering, and analytics teams, with a focus on enterprise data platforms and