About This Role
This Research Scientist 2 role is part of Humana's Clinical Innovation and Trend Analytic Team, which focuses on improving clinical outcomes and lowering costs for Medicare Advantage beneficiaries. The team uses an evidence-based approach with data analytics, clinical expertise, and rigorous study designs. The role involves applying statistical and epidemiologic principles to identify trends, assess cause-effect relationships, and size potential opportunities using complex data, working closely with strategy partners and clinicians.
Responsibilities
- Do exploratory analysis on populations, trends, and clinical conditions to inform potential opportunities for trend savings and clinical outcomes improvement for members
- Collaborate with clinicians and clinical informaticists to define various clinical concepts and extract clinical information from medical, pharmacy, and lab claims for analytics and modeling purposes
- Leverage a wide range of analytics methods from descriptive analysis to epidemiological methods
- Design outcomes studies and perform program evaluation using randomized controlled trials, propensity matching, difference-in-difference models, or other experimental/quasi-experimental methods
- Conduct literature reviews and intervention research to assess engagement rates and treatment effect sizes of interventions that are in the early stages of design and implementation
- Write code in SQL, SAS, and Python to assemble data, create analytic variables/features, design visuals and charts, and statistical models for research/science use-cases
- Translate analytic results into key takeaways with actionable insights and communicate to business partners
- Understand department, segment, and organizational strategy and operating objectives, including their linkages to related areas
- Make decisions regarding research methods, occasionally in ambiguous situations with general guidance
Requirements
- Master's Degree in a quantitative discipline such as Epidemiology, Biostatistics, Economics, Statistics, Clinical Informatics, Engineering, and/or related fields
- 2+ years of experience that includes:
- Skills to create datasets and analytical variables from large and complex data environments by writing code in SQL, SAS, and Python
- Applying research methods to transform high volumes of complex data into actionable insights
- Experience with experimental and quasi-experimental methods such as randomized controlled trials, propensity matching, or difference-in-difference models
- Strong interest in healthcare and desire to make a positive impact on health outcomes
- Ability to work collaboratively within a multi-disciplinary team, to deliver quality analytical work, and communicate results and insights clearly to business partners
