Lead Data Scientist - Agentic AI

Salary: $122,100 - 162,800 per year Requirements:

• We require a masters degree or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Data Science, or another quantitative discipline.
• We look for 7–10+ years of experience in data science or advanced analytics, with substantial hands-on work in Generative AI and LLM-based systems.
• We need proven experience designing, building, and deploying production-grade ML and GenAI solutions, including LLMs, RAG architectures, and AI-powered automation.
• We expect strong Python skills and familiarity with modern ML frameworks such as PyTorch, TensorFlow, and/or Hugging Face.
• We value deep knowledge of machine learning algorithms, statistical modeling, experimental design, and data structures.
• We want experience with cloud platforms, preferably Azure, with AWS or GCP also acceptable, as well as MLOps practices.
• We need the ability to communicate complex technical concepts clearly to both business and technical audiences.
• We look for demonstrated leadership in driving initiatives, influencing stakeholders, and mentoring colleagues.

• We lead the full lifecycle of Generative AI and agentic AI solutions, from ideation and research through prototyping, implementation, evaluation, deployment, and production support.
• We design and build scalable GenAI systems such as LLM applications, Retrieval-Augmented Generation solutions, AI agents, and intelligent automation workflows.
• We promote best practices in prompt engineering, LLM evaluation, fine-tuning approaches, and secure model hosting where relevant.
• We apply advanced data science and machine learning methods across predictive modeling, forecasting, classification, anomaly detection, recommendation systems, NLP, and GenAI-enabled analytics.
• We develop custom ML models and analytical frameworks for complex healthcare and enterprise data challenges.
• We perform exploratory data analysis, feature engineering, and statistical analysis to uncover actionable insights and inform solution design.
• We collaborate with engineering and platform teams to deploy, monitor, and maintain ML and GenAI solutions in production using cloud-native and MLOps best practices.
• We establish model performance tracking, drift detection, reliability monitoring, and continuous improvement processes for deployed models and AI agents.
• We ensure solutions are scalable, cost-efficient, resilient, and aligned with enterprise architecture standards.
• We maintain strong model governance, documentation, and auditability across all ML and GenAI solutions.
• We apply Responsible AI principles, including explainability, transparency, data privacy, security, and regulatory compliance, especially in healthcare settings.
• We guide the safe, compliant, and ethical use of LLMs and agentic AI across enterprise use cases.
• We partner closely with business stakeholders and product managers to turn requirements into analytical problem statements, solution designs, and delivery roadmaps.
• We present technical solutions, insights, and status updates to technical and non-technical audiences, including senior leadership.
• We mentor and support junior data scientists and engineers, encouraging technical excellence, innovation, and continuous learning.

• AI
• AWS
• Azure
• Cloud
• GCP
• Support
• LLM
• Machine Learning
• PyTorch
• Python
• Security
• TensorFlow
• Architect

More:

We are McKesson, an impact-driven Fortune 10 healthcare company that works across nearly every part of healthcare to make quality care more accessible and affordable. We foster a culture where our people can grow, make an impact, and contribute new ideas as we shape the future of health for patients, communities, and one another. For this role, we offer a competitive total rewards package, including potential bonus and long-term incentive opportunities, along with a base pay range of $122,100 to $162,800. We are committed to equal employment opportunity and welcome applicants from all backgrounds, including individuals with disabilities.

last updated 32 week of 2026