Data Scientist, Operations Research

What Data Science contributes to Cardinal Health The Data and Analytics Function oversees the analytics life-cycle in order to identify, analyze and present relevant insights that drive business decisions and anticipate opportunities to achieve a competitive advantage. This function manages analytic data platforms, the access, design and implementation of reporting/business intelligence solutions, and the application of advanced quantitative modeling. Data Science applies base, scientific methodologies from various disciplines, techniques and tools that extracts knowledge and insight from data to solve complex business problems on large data sets, integrating multiple systems. Department/Team Overview We are looking for a Data Scientist, Operations Research Analyst to join our Decision Science Solutions (DS2) team. Our mission is to improve our pharmaceutical supply chain’s performance to better service our pharmacy customers, so that they can focus on their patients. The DS2 team consists of Supply Chain Data Scientists, Operations Research Analysts, Data Analysts, and Data Engineers. We work cross-functionally to solve problems leveraging a variety of skillsets and perspectives to achieve the best outcomes. We perform analyses, recommend solutions, and build products to enable better decision making in the following areas: Distribution center network design and capacity planning Facility layout and design; warehouse capacity and utilization Warehouse process improvement Labor management and automation Inventory management: stocking strategies and replenishment policies Transportation planning: first mile, middle mile, and final mile Sales and operations planning (resource management in response to demand changes) Responsibilities As a Data Scientist in Supply Chain Operations, you will apply your knowledge of business processes, systems, data, and analytical tools to explore and identify root causes of problems. You will forecast future demand, build optimization and simulation models, and communicate actionable insights. You will work with cross-functional project teams to ideate, develop, and recommend solutions. Specific responsibilities are to: Listen to clients and ask questions to clearly define business problems. Perform exploratory analysis to determine root causes of problems and confirm/disprove hypotheses. Develop predictive models to forecast future volumes that will drive capacity/resource needs. Develop customer and product segmentation models and design our supply chain to support differentiated services. Build optimization and simulation models to recommend capacity investments, resource plans, policy changes, and process changes to improve supply chain performance. Develop prescriptive models using 3rd party optimization/simulation software and custom-build models. Recommend solutions. Summarize the financial and operational impact of the recommendation and pros/cons of alternatives considered. Work with Data Engineers to create data models for analyses.

2-4 years of experience, preferred Bachelor's degree in a quantitative field, or equivalent work experience, preferred MS/MBA with focus in Data Science, Operations Research, Industrial Engineering, or Statistics preferred Demonstrated ability to apply Data Science and Operations Research techniques to logistics and supply chain management problems preferred Experience with Structured Query Language (SQL) and working with databases preferred Experience with data analysis tools such as R, Python, SQL, Alteryx, Tableau, and SAS preferred Experience with Strategic Network Design, Simulation (e.g., AnyLogic), or Mathematical Programming (e.g., CPLEX) software preferred Ability to work as part of a team as the key analytical resource Excellent communication skills with an ability to explain quantitative analysis in simple business terms Intellectual curiosity, humility, genuine respect and desire to help others Bias for action and passion for