Job Description
The Data Scientist role supports the development of analytic solutions across McKesson. Our team applies data science methodologies to interdisciplinary business problems across Finance, Operations, Accounting, and Supply Chain.
Position Objectives
* Develop machine learning solutions to support new business initiatives and facilitate next best actions.
* Architect and lead implementation of driverless forecasting systems, leveraging best data science practices and technologies.
* Lead DevOps of new and existing models, leveraging cloud/open-source technologies.
Key Responsibilities
Analytic Responsibilities
* Develop inventory optimization/multi-echelon simulation framework for supply chain.
* Support Transportation organization's forecasting and optimization needs around route selection and late delivery prediction.
* Fully automate existing forecasting solutions.
* 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.
Requirements
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.
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 object-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.