About the Role
We are looking for a Data Engineer to join the Data Science & Engineering (DSE) team, which is developing EntityRisk’s core methodology and software. Our proprietary platform estimates the individual benefits of treatment—through advanced modeling techniques and integrated clinical trial, genomic, and real-world data. As part of the DSE team, your work will be foundational to our product offerings, some of which include:
- Analysis of all current and potential surrogate measures and their connections to critical endpoints of value to patients and payers
- Customized individual and subpopulation-level survival and treatment duration curves
- Scenario planning for pipeline and inline assets
- Event and cash flow forecasting and analytics for efficacy-linked instruments
- Value modeling
The Data Engineer position is a role for candidates with a bachelor’s or master’s degree in a quantitative field such as statistics, economics, mathematics, finance, or computer science and experience working with claims data ETL pipelines.
Data Engineers are responsible for building infrastructure to automate the ingestion of multiple claims and other healthcare data feeds into a common data model. They write ETL scripts, stand up and manage AWS resources on which the work is executed, and respond to requests for support from both platform developers and individual researchers.
Ideal candidates are collaborative, intellectually curious, and experienced with healthcare data feeds. Successful candidates will have good written and verbal communication skills in addition to strong technical skills.
Responsibilities
- Build data pipelines that take in a range of real-world (e.g., medical claims, electronic health records) or clinical trial data assets and create output in the form of analytic datasets using relevant tools (e.g., SQL, Python, etc.)
- Manage AWS computing resources for both ETL and data science / machine learning applications
- Contribute to internal software libraries by implementing new modeling features, creating unit tests, writing documentation, and enforcing style conventions
- Follow software best practices including version control (Git), code review, and continuous integration
Qualifications
- BA/BS or MS in a quantitative field
- Fluency in at least one of R, Python, or SQL
- 2+ years experience performing ETL operations on healthcare data
- Familiarity with AWS virtual private cloud or similar cloud computing environment
- Experience with the OMOP common data model preferred, but not required