Sr. Data Scientist - Pricing

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 Data Scientist role will support the development of analytic solutions across McKesson.
Our team applies data science methodologies to interdisciplinary business problems across Finance, Operations, Accounting, & Supply Chain. This position will work closely with multiple business units such as Treasury, FP&A, Operations, and Pricing. The position’s objectives are:
• Develop machine learning solutions to support new business initiatives / facilitate next best actions
• Architect and lead implementation of driverless forecasting systems, levering best data science practices and technologies
• Lead DevOps of new and existing models, leveraging cloud / open-source
technologies
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
• Create and implement predictive models to analyze pricing data and forecast trends.
• Utilize machine learning algorithms to optimize pricing structures.
• Lead in development of statistical simulation decision frameworks.
• Build time series models leveraging techniques such as Sarima, Prophet, Holt-
Winters, Transformers.
• Design and guide implementation of model variance analysis and impact tracking framework
• Lead in deploying statistical models in production
• Lead in development of statistical simulation decision frameworks

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: 5+ years data science / analytics / programming experience based on
combination of industry and academic experience
Education: bachelor’s degree in a technical field such as: Computer Science, Statistics,
Applied Mathematics, Finance, Economics or related quantitative / STEM majors. Masters
and/or PhD preferred.
Critical Skills
• 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 (Python, R)
• 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 distrib