Lead Data Analyst, AI Big Bets

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you.

Current Need

We are recruiting for a Lead Data Analyst, AI Big Bets to join our team!

This role is instrumental in enabling rapid AI and ML model prototyping by ensuring data is readily available for AI and ML experts. It involves creating efficient data pipelines and impactful visualizations to support strategic decision-making and accelerate model development.

Key Responsibilities:

Lead Data Analysis for AI Big Bets Rapid Experimentation

• Architect and build scalable data pipelines in alignment with AI Big Bets initiatives for rapid AI/ML prototyping

• Ensure secure, compliant data governance standards to support fast experimentation

• Optimize data architecture for efficiency and scalability, serving as the expert in data storage and retrieval

• Collaborate directly with AI and ML experts to ensure data accessibility for model development

• Engage in hands-on development and maintenance of data infrastructure to drive AI/ML innovation

Collaborative Leadership & Stakeholder Engagement:

• Collaborate closely with AI researchers, data scientists, product teams, and leadership, aligning data strategies with overarching business objectives.

• Communicate complex technical insights to non-technical stakeholders, ensuring clarity and alignment across all levels of the organization.

Strategic Data Visualization & Reporting:

• Lead the creation of dashboards and reports, transforming complex data insights into strategic business intelligence for leadership.

Continuous Improvement & Innovation:

• Stay at the forefront of industry trends in data engineering, AI, and visualization, continuously enhancing your skill set and knowledge base.

Minimum Requirements

Typically requires 10+ years of relevant experience

Critical Skills

• Mastery in designing and maintaining ETL/ELT pipelines, data lakes, and data warehouses.

• Proficiency in programming languages such as Python, SQL, and Scala.

• Expertise in platforms like Azure, Snowflake, and Databricks, with a strong understanding of data privacy, compliance, and governance.

• Advanced skills in Power BI, Tableau, or similar tools for executive-level reporting.

• Experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra), API integration, and workflow automation.

Additional Skills

• Experience working in AI/ML-driven environments, supporting rapid experimentation and model deployment (familiarity with Delta Lake, Azure Data Factory is a plus).

• Demonstrated progression to senior levels through recognized expertise and contributions to team and organizational success.

• Experience supporting AI/ML initiatives by enabling data access, transformation, and visualization to drive strategic decision-making.

• Proven ability to work in fast-paced environments, supporting quick iteration and validation of AI-driven use cases.

• Experience creating high-impact dashboards and reports tailored for leadership review and decision-making.

• Experience working closely with AI researchers, data scientists, product managers, and business stakeholders to align data strategies with business goals.

• Background in technology, finance, healthcare, e-commerce, or other data-intensive industries where AI and analytics play a critical role.

• Understanding of how data engineering and visualization contribute to business value, efficiency, and revenue growth.

• Experience implementing new data processes, and visualization tools in evolving business environments.

Education

• Bachelor’s degree required in a quantitative field such as Statistics, Computer Science, Economics, Operations Research, Engineering, Applied Mathematics or related field. MBA or Master’s degree in a quantitative field preferred OR equivalent experience.