Senior Data Scientist - Pharmacy Operations

• Develops and/or uses algorithms and statistical predictive models and determines analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes
• Performs analyses of structured and unstructured data to solve multiple and/or complex business problems utilizing advanced statistical techniques and mathematical analyses and broad knowledge of the organization and/or industry
• Collaborates with business partners to understand their problems and goals, develop predictive modeling, statistical analysis, data reports and performance metrics
• Develops and participates in presentations and consultations to existing and prospective constituents on analytics results and solutions
• Interacts with internal and external peers and managers to exchange complex information related to areas of specialization
• Use strong knowledge in algorithms and predictive models to investigate problems, detect patterns and recommend solutions
• Use strong programming skills to explore, examine and interpret large volumes of data in various forms

• 3+ years of relevant analytic experience
• Experience programming using Python
• Experience in SQL
• Demonstrates strong ability to communicate technical concepts and implications to business partners
• Anticipates and prevents problems and roadblocks before they occur
• Strong knowledge of advanced analytics tools and languages to analyze large data sets from multiple data sources
• Demonstrates proficiency in most areas of mathematical analysis methods, machine learning, statistical analyses, and predictive modeling and in-depth specialization in some areas

Master’s degree or PhD preferred

• Affordable medical plan options
• 401(k) plan (including matching company contributions)
• Employee stock purchase plan
• No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching
• Paid time off
• Flexible work schedules
• Family leave
• Dependent care resources
• Colleague assistance programs
• Tuition assistance
• Retiree medical access