Data Scientist Senior

Elevance Health•Indianapolis, IN

3d•Hybrid

About The Position

The Data Scientist Senior develops and implements predictive modeling algorithms and techniques to solve complex business problems and optimize member experiences. The role leads predictive modeling projects in consultation with business partners, processes large data streams in distributed computing environments, recommends batch and real-time model scoring, and oversees development of proprietary algorithms and customized solutions. It also develops advanced visualizations, communicates results and limitations, provides actionable insights, improves existing modeling algorithms, and collaborates with business partners to identify population segments and patterns related to quality, use, cost, and other variables. The position mentors other data scientists. This hybrid role requires associates to work in-office one day per week. The preferred location is the Pulse Point office in Indianapolis, Indiana; alternate locations may be considered for candidates within commuting distance of an office. Candidates outside a reasonable commuting distance will not be considered unless an accommodation is granted as required by law.

Requirements

Bachelor’s degree in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics, or a related quantitative discipline, and at least 5 years of experience in predictive analytics or equivalent; an equivalent combination of education and experience is also accepted.

Nice To Haves

Consulting experience.
Expert knowledge of SAS, SAS Enterprise Miner Lead, and programming languages such as Python and R.
Experience leading end-to-end data science project implementation.
Experience managing a small team through a formal or informal reporting relationship.
PhD and experience in the healthcare sector.

Responsibilities

Design and lead predictive modeling projects addressing complex business problems in consultation with business partners.
Facilitate analysis by piping and processing massive data streams in distributed computing environments such as Hadoop.
Recommend appropriate batch and real-time model scoring to drive actions.
Oversee development of proprietary algorithms and customized solutions that go beyond standard industry tools.
Develop advanced visualizations of analysis output for business users.
Publish results and address constraints and limitations with business partners.
Provide actionable insights to ensure established targets are met.
Identify continuous improvement opportunities for current predictive modeling algorithms.
Collaborate with business partners to identify population segments and develop actionable plans for finding patterns related to quality, use, cost, and other variables.
Mentor other data scientists.