Research Scientist, Clinical Innovation & Trend Analytics
New
H
HumanaHealthcare analytics
Source API remote eligibility restrictions: United StatesFull-TimeMiddle
Salary$78,400 - $107,800 per year. This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance.
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Job Details
- Experience
- 2+ years of experience
- Required Skills
- PythonSQLPySpark
Requirements
- Master's degree in a quantitative discipline such as Epidemiology, Biostatistics, Economics, Statistics, Clinical Informatics, or Engineering, or a related field.
- At least 2 years of relevant experience.
- Experience writing SQL, SAS, and Python to create datasets and analytical variables from large, complex data environments.
- Experience applying research methods to turn complex data into actionable insights.
- Experience with experimental or quasi-experimental methods, such as randomized controlled trials, propensity matching, or difference-in-difference models.
- Experience collaborating in multidisciplinary teams and communicating analytical results and insights clearly to business partners.
- Healthcare or managed care experience is preferred.
- Experience with medical, pharmacy, and lab claims is preferred.
- Familiarity with clinical concepts across conditions and disease states is preferred.
- Familiarity with hypothesis testing, statistical methods, or comparative effectiveness study design and modeling is preferred.
- Experience with PySpark, Databricks, Microsoft Azure, or Power BI is preferred.
Responsibilities
- Conduct exploratory analyses of populations, trends, and clinical conditions to identify opportunities for savings and improved clinical outcomes.
- Collaborate with clinicians and clinical informaticists to define clinical concepts and extract information from medical, pharmacy, and lab claims.
- Apply descriptive and epidemiological analytics methods.
- Design outcomes studies and evaluate programs using randomized controlled trials, propensity matching, difference-in-difference models, or other experimental or quasi-experimental methods.
- Review literature and research interventions to assess engagement rates and treatment effect sizes.
- Write SQL, SAS, and Python code to assemble data, create analytic variables and features, build visualizations, and develop statistical models.
- Translate analytical results into actionable insights for business partners.
- Make research-method decisions, including in ambiguous situations, with general guidance.
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