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Job Title: AI/ML Lead – Supply Chain

Position Summary:

Mckesson's AI/ML Lead - Supply will be responsible for building Supply Chain solutions to deliver incremental business value, through improved operational efficiencies and enhanced business effectiveness. Engage in rapid solution architecture and prototyping of data science models, working closely with internal business partners to quickly transform concepts into actionable insights that clearly illustrate potential incremental business value.

Key Responsibilities:

Exploratory Analysis and Data Wrangling:

• Identify critical data points aligned with business objectives.
• Assess data quality and integrity using statistical testing, ensuring readiness for rapid experimentation.
• Apply modeling techniques to extract insights, identify patterns, and detect anomalies.
• Communicate insights effectively through visualization, aligning the data story with business stakeholders while highlighting potential risks or roadblocks for further experimentation.

Rapid Experimentation Enablement:

• Lead and facilitate collaborative sessions with internal business partners to brainstorm, define, and refine analytics solution requirements.
• Identify optimal modeling techniques that balance time efficiency and computational efficiency based on business needs.
• Develop rapid prototype analytics solutions, including but not limited to statistical testing, machine learning, deep learning, simulation, operations research, and reinforcement learning, while evaluating development effort and computing costs.

Business impact valuation:

• Quantify business impact using hypotheses and assumptions.
• Evaluate scalability of experiments to production-ready products or enterprise-level solutions.
• Estimate complexity and ROI, balancing time, resources, and potential business value.
• Identify opportunities for reuse, enabling broader adoption of experimental insights across the enterprise.

Collaboration & Stakeholder Engagement:

• Work closely with AI researchers, data analysts, data engineers, data scientists, product teams, and leadership to align on data/infrastructure readiness, business objective, solution architecture, experiments, measure of success
• Communicate technical insights to non-technical stakeholders, ensuring clarity and impact.
• Foster a data-driven culture by promoting digital mindset and AI-Data driven decision making

Job Qualifications (Must have skills, & Qualifications):

• 10+ years data science / analytics / programming experience based on combination of industry and academic experience.
• Knowledge of relational databases (SQL Server, Snowflake, Databricks, Oracle, SAP), cloud computing platforms (Azure, Databricks), and simulation, optimization and operation research (Monte Carlo simulation, solvers)
• Bachelor’s degree in a technical field such as: Operations Research, Computer Science, Statistics, Applied Mathematics, Engineering or related quantitative / STEM majors (or equivalent work experience). Master’s and/or PhD preferred.

Business Experience:

• Leverage statistical methods and advanced modeling techniques (e.g., regression, classification, clustering, anomaly detection, time series, Bayesian inference, NLP, pre-trained models, neural networks, simulation, operation research) to extract insights and drive informed decision-making.
• Thrive in fast-paced environments, enabling rapid iteration and validation of AI-driven use cases. Lead and facilitate sessions with internal business partners to brainstorm, define, and refine analytics solutions. Assess data availability and readiness, utilizing statistical analysis, AI/ML modeling, design of experiments, and process flow mapping to support decision-making. Develop early-stage prototypes, evaluate solution feasibility and applicability, and identify potential risks and roadblocks to ensure a collaborative, iterative, and dynamic approach.
• Work closely with project managers, product owners, technology teams, and business stakeholders to leverage analytics in shaping corporate Supply Chain strategy. Demonstrated ability to tackle challenges across the entire data stack, from data wrangling to strategic decision-making.

Specialized Knowledge/Skills:

• Hands-on experience in statistical simulation decision frameworks; understanding of linear / non-linear programming
• Preferably hands on experience with enterprise-scale digital twin, inventory policy, network optimization
• Understanding of reinforcement learning and its application in supply chain / transportation / inventory management is a plus

Working Conditions: Traditional office environment, Large percent of time performing computer based work is required.

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

McKesson is an Equal Opportunity Employer

McKesson provides equal employment opportunities to applicants and employees and is committed to a diverse and inclusive environment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age or genetic information. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.

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