Principal Data Scientist - Supply Chain

Overview

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.

The Principal Data Scientist 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 end to end supply chain use case. The position's objectives are:

• Lead development of a best-in-class out-of-stock prediction application, enhance McKesson's demand sensing capabilities and drive optimal inventory allocations
• Utilize advanced analytics, machine learning, and predictive modeling to identify trends, risks, and opportunities within our supply chain
• Lead development of causal inference methodologies to evaluate impact of inventory actions

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

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.

• Lead development of AI/ML driven continuous monitoring systems to dynamically track McKesson network and continuously identify areas of working capital opportunity
• Play a leading role in adding Reinforcement Learning optimize decision-making
• Develop inventory optimization / multi-echelon simulation framework for supply chain

• 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

• 10+ years data science / analytics / programming experience based on combination of industry and academic experience
• Bachelor's degree in a technical field such as Operations Research, Computer Science, Statistics, Applied Mathematics, Economics, Engineering or related quantitative / STEM majors (or equivalent work experience). Master s degree and/or PhD preferred.

• Demonstrated expertise with time series forecasting
• Deep knowledge of statistical methods and advanced modeling techniques (e.g., SVM, Random Forest, Bayesian inference, graph models, NLP, Computer Vision, neural networks, etc.) along with the optimization and OR techniques
• 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.

• 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. 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 .

Our Base Pay Range for this position

$184,400 - $307,300