Lead Data Scientist - Operations Research

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.

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The Lead Data Scientist, Operations Research role is responsible for architecting and implementing AI/ML products to enhance the efficiency and effectiveness of McKesson's supply chain operations as part of a McKesson's Supply Chain & Operations Research COE.

Our team applies data science methodologies to interdisciplinary business problems across Operations & Supply Chain. This position will work on strategic in-flight use cases around inventory and working capital management. The position's objectives are:

• Develop stochastic models to facilitate next best actions across Supply Chain
• Architect and lead implementation of AI/ML driven operation research frameworks to optimize enterprise inventory management systems
• Lead development of enterprise-scale digital twin for inventory management

The candidate should possess the ability to perform statistical modelling techniques and derive business insights that are required to drive analytic innovation at McKesson. The candidate should also be an active learner able to grasp and apply new analytic approaches, as well as mentor junior / developing resources.

Position Description

The purpose of this position is to architect, implement, drive adoption, and measure impact of innovative analytic solutions at McKesson, as well as make significant improvements to existing solutions.

Analytic Responsibilities

• Develop inventory optimization / multi-echelon simulation framework for supply chain
• Lead in development of statistical simulation decision frameworks
• Develop of AI/ML driven continuous monitoring systems in order to dynamically track McKesson network and continuously identify areas of working capital opportunity
• Play a leading role in adding Reinforcement Learning to set dynamic prices & safety stocks

Other Responsibilities

• Support stakeholders' analytic needs, gather user requirements, help drive adoption
• Cultivate business development opportunities
• Assist in developing and maintaining long-term stakeholder relationships and networks

Minimum Requirements

Experience: 7+ years data science / analytics / programming experience based on combination of industry and academic experience

Education: bachelor's degree in a technical field such as: Operations Research, Computer Science, Statistics, Applied Mathematics, Engineering or related quantitative / STEM majors. Masters and/or PhD preferred.

Critical Skills

• Experience with one or more of optimization toolkits/libraries like CPlex, Gurobi, XPressMP, Open-source solvers (CBC, GLPK) etc
• Deep knowledge of statistical methods, advanced modeling techniques, along with optimization & OR techniques
• Demonstrated experience with solving enterprise inventory optimization and/or transportation optimization problems
• Ability to communicate your results from deeply technical to non-technical audiences
• Demonstrated ability to tackle problems across the full data stack, from data wrangling (leveraging SQL or other methodologies) to stakeholder consumption at scale
• Deep knowledge of machine learning / data science best practices
• Knowledge of statistical programming (SAS, R, MATLAB)
• Ability to communicate technical concepts to non-technical audiences
• Demonstrated experience with objected oriented programming (Python, Java, C#, VBA, etc.)
• Strong grasp of fundamental statistical concepts: linear regression, A/B testing, outlier analysis, probability distributions, tests for independence, etc.

Additional Knowledge & Skills

• Analysis/Process Thinking
• Team player
• Strong verbal and written communication
• Knowledge of relational databases (e.g. MS SQL Server, Snowflake, Oracle)
• Knowledge of cloud computing platforms is a plus (e.g. Azure, AWS, Google Cloud, Databricks)
• Proficient with Excel spreadsheets, financial modeling, and reporting
• Prior data mining experience using enterprise systems (SAP or JD Edwards preferred)
• Knowledge of data warehousing & ETL best practices is a plus

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. 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

$154,700 - $257,900

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.

Join us at McKesson!