Lead Technical Project Manager

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Lead Technical Project Manager

Summary

The Lead Technical Project Manager plays a critical role in driving the successful delivery for AI/ML & Advanced Analytics initiatives across the organization. This role bridges business stakeholders, data science teams, and engineering groups to ensure projects are aligned with strategic objectives, well-scoped, and delivered on time. The TPM will manage the end-to-end project lifecycle including intake of requests, requirement gathering, prioritization, roadmap development, milestone tracking, and status communication to leadership.

What You’ll Do

- Program Leadership & Road Mapping – Define and own the end-to-end roadmap for AI/ML initiatives, translating business objectives into actionable programs such as demand forecasting models, NLP-driven chatbots, or predictive analytics. Manage the intake of new requests, gather necessary information for accurate sizing, confirm business value, and ensure alignment with strategic priorities. Evaluate and prioritize initiatives by balancing business value, technical feasibility, resource availability, and associated risks. Use portfolio management tools (Jira, Confluence, MS Project, Smartsheet) to maintain visibility and alignment from ideation through deployment.

- Cross-Functional Orchestration – Serve as the central coordinator, orchestrating collaboration across data scientists, ML engineers, data engineers, business analysts, and IT teams. Ensure high-quality pipelines and seamless integration into production systems through APIs, cloud ML services, and CI/CD pipelines.

- Execution & Delivery Management – Oversee day-to-day delivery of AI/ML projects using Agile practices (Scrum, SAFe, Kanban). Manage sprints, backlogs, epics, and stories within Jira/Confluence, tracking dependencies and deliverables. Identify risks (e.g., limited data availability, model performance gaps, infrastructure bottlenecks) and implement mitigation strategies. Enforce robust testing standards including unit testing, model validation, A/B testing, and performance benchmarking.

- Business Alignment & Stakeholder Management – Act as a trusted partner to business stakeholders and product teams, translating business use cases into clear technical AI/ML requirements. Establish measurable KPIs (accuracy, ROI, adoption rates, productivity impact). Provide regular executive-level updates, communicating technical progress clearly and concisely.

- Governance & Compliance – Ensure compliance with regulatory frameworks (HIPAA, GDPR, SOC 2, FDA). Promote Responsible AI principles (fairness, transparency, explainability). Drive documentation, audit readiness, model cataloging, data lineage traceability, and reproducibility. Establish governance for MLOps including model versioning, drift monitoring, and automated retraining.

- Metrics & Reporting – Define and track KPIs across technical, business, and delivery dimensions (accuracy, precision/recall, F1 score, ROI, adoption). Provide transparent portfolio health reporting to leadership.

- Innovation Enablement – Champion innovation by promoting emerging technologies (Generative AI, LLMOps, AutoML). Collaborate with architecture teams to modernize ML stack (Databricks Lakehouse, Vertex AI, Azure ML). Drive accelerators such as reusable code libraries, pre-trained models, and standardized MLOps pipelines.

What You Bring

- Strong technical acumen in AI/ML and analytics

- Excellent project management skills

- Ability to communicate effectively with technical and non-technical audiences
- Proven ability to align cross-functional teams and remove delivery bottlenecks

Minimum Requirements

- Degree or equivalent and typically requires 10+ years of relevant experience. Less years required if has relevant Master’s or Doctorate qualifications.

Preferable Skills & Experience

- Experience with Generative AI, LLMOps, AutoML

- Familiarity with platforms like Databricks, Vertex AI, Azure ML

- Knowledge of governance frameworks and Responsible AI principles

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here.

Our Base Pay Range for this position

$134,900 - $224,800

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McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.

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McKesson is an Equal Opportunity Employer

McKesson provides equal employment opportunities to 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. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.

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