Address
Form of workJob Type
Full-time
Description
Provide strategic leadership for the development, validation, and delivery of algorithms, statistical models, and reporting tools. Act as the analytic team lead for highly complex projects involving multiple resources and tasks, providing individual mentoring in support of company objectives. Lead development and execution of new and/or highly complex algorithms and statistical predictive models and determines analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes. Establish analytical rigor and statistical methods to analyze large amounts of data, using advanced statistical techniques and mathematical analyses. Manage highly complex analytical projects from data exploration, model building, performance evaluation, and testing. Apply in-depth knowledge of systems and products to consult and advise on additional efforts across organization and enterprise. Motivate team members and probes into technical details, and mentor others to do the same. Provide thought leadership and direction for analytic solutions, tools, and studies. Anticipate and solve strategic and high-risk business problems with a broad impact on the business area by applying leading-edge theories and techniques to investigate problems, detect patterns, and recommend solutions. Provide guidance to develop an enterprise-wide analytics strategy and roadmap. Interact with internal and external peers and management to share highly complex information and solutions related to areas of expertise and/or to gain acceptance of new or enhanced technology and business solutions. Telecommuting permitted. Travel Requirements: 10% international travel.
Requirements
This position requires a Master's degree, or its foreign equivalent, in Data Science or a related field, plus 3 years of experience as a Data Scientist in a Pharmacy Benefit Management or related occupation. Additionally, the applicant must have professional experience with: 1) Utilizing visualization tools like PowerBI, Tableau, Python to simplify insight discovery and improve reporting, and utilizing data tools like service AAS to empower data-driven decision-making across the business; 2) Developing Data Science applications in Python and R and deploying them to cloud environments; 3) Performing statistical analysis, leveraging deep understanding of data, customers, and business, to hypothesize and recommend product enhancements; 4) Utilizing Machine Learning and Deep Learning frameworks to enhance products and enable tactical and strategic development and consulting; 5) Using emerging Data Science trends to identify implications and proactively develop best-in-class processes and techniques to leverage Data Science across consumer touchpoints; 6) Working with business leaders to convert strategic goals into actionable roadmaps and identify needs to develop a plan of action; 7) Facilitating effective access to data and analytical resources by partnering with IT, Account Management, Business Development, Clinical, or Finance teams; 8) Using experimentation techniques like Statistical Analysis, Hypothesis testing, Machine Learning, Funnel analysis, A/B testing, etc. to drive product engagement and improve customer experience; and 9) Developing processes and approaches to improve the effectiveness and visibility of Data Science.
