About The Company 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.

About The Role McKesson Corporation is seeking a highly skilled and innovative Lead Data Scientist with experience in Generative AI development. This pivotal role involves leading the design, development, and deployment of advanced machine learning and Generative AI solutions to address complex healthcare challenges. The successful candidate will leverage cutting-edge AI techniques to drive business transformation, enhance operational efficiency, and improve patient outcomes.

You will work closely with cross-functional teams, including engineering, product management, and business stakeholders, to translate strategic objectives into scalable AI solutions. This position offers an exciting opportunity to influence the future of healthcare technology by deploying innovative AI models and systems that make a tangible difference in the industry.

Qualifications The ideal candidate will possess a master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Data Science, or a related quantitative field. You should have 7 to 10+ years of experience in data science or advanced analytics, with significant hands-on experience in Generative AI and large language models (LLMs). Proven expertise in designing, building, and deploying production-grade ML and GenAI solutions, including LLMs, Retrieval-Augmented Generation (RAG), and AI-driven automation, is essential.

Strong proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, or Hugging Face is required. A deep understanding of machine learning algorithms, statistical modeling,



experimental design, and data structures is necessary.

Experience working with cloud platforms, particularly Azure, and familiarity with MLOps practices are highly desirable. Excellent communication skills to articulate complex technical concepts to diverse audiences, along with demonstrated leadership and mentorship capabilities, will set candidates apart.

Responsibilities Lead the end-to-end lifecycle of Generative AI and agentic AI solutions, including ideation, research, prototyping, implementation, evaluation, deployment, and ongoing support.

Architect and develop scalable GenAI systems such as LLM-based applications, Retrieval-Augmented Generation (RAG), AI agents, and intelligent automation workflows to optimize decision-making, operational efficiency, and customer outcomes.

Drive the adoption of best practices in prompt engineering, LLM evaluation, fine-tuning strategies, and secure model hosting to ensure robust and ethical AI deployment.

Apply advanced data science and machine learning techniques across various use cases, including predictive modeling, forecasting, classification, anomaly detection, recommendation systems, NLP, and GenAI-enabled analytics.

Develop custom ML models and analytical frameworks tailored to complex healthcare and enterprise data challenges, ensuring solutions are creative and effective.

Perform exploratory data analysis (EDA), feature engineering, and statistical analysis to generate actionable insights and inform solution design.

Collaborate with engineering and platform teams to deploy, monitor, and maintain ML and GenAI solutions in cloud environments, adhering to MLOps best practices.

Establish model performance tracking, drift detection, reliability monitoring, and continuous improvement processes for deployed models and AI agents.





Ensure solutions are scalable, cost-efficient, resilient, and aligned with enterprise architecture standards.

Maintain strong model governance, comprehensive documentation, and auditability across all AI solutions.

Apply Responsible AI principles, including explainability, transparency, data privacy, security, and regulatory compliance, especially within healthcare contexts.

Guide safe, compliant, and ethical use of LLMs and agentic AI across enterprise use cases.

Work closely with business stakeholders and product managers to translate requirements into clear problem statements, solution designs, and execution plans.

Present technical solutions, insights, and progress updates to both technical and non-technical audiences, including senior leadership.

Mentor and develop junior data scientists and engineers, fostering a culture of innovation, technical excellence, and continuous learning.

Benefits McKesson offers a competitive total rewards package designed to support your professional growth and personal well-being. Our benefits include comprehensive health insurance, retirement savings plans, paid time off, and wellness programs. We also provide opportunities for continuous learning and development through training, certifications, and career advancement programs.

As part of our commitment to work-life balance, we promote flexible working arrangements and a supportive work environment. Additional perks may include performance bonuses, long-term incentive opportunities, and employee recognition programs. Our goal is to create an inclusive environment where every employee feels valued and empowered to contribute to our mission of improving healthcare for all.

Equal Opportunity McKesson is an Equal Opportunity Employer committed to diversity and inclusion. We provide equal employment opportunities to all applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. We believe that a diverse workforce enriches

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