Remote, 12-month renewable contract
As a Sr programmer/analyst, Real-World Data and Analytics, you will conduct hands-on programming (expert level for R and/or Python and SQL, proficiency with SAS is a plus) in supporting our real-world data & analytics needs under the supervision of our Director HEOR analytics scientists. This role will support the development of analytical processes using new data assets. Additionally, this role will support RWD needs across therapeutic areas by addressing research questions from senior MD executives.
- Respond to HEOR Director’s request timely.
- Understand query, analytics requests and study specifications
- Proactively clarify requests and ensure accurate implementation of protocols and analytical specifications.
- Conduct queries to EHR, claims and/or other real-world data sources
- Has a keen sense of identifying outliers, and anomalies.
- Ensure high-quality work products
- Keep detailed documentation and generate results with a clear and professional presentation
- Detail-oriented with excellent communication skills. At ease with an abundance of detail and complexity, yet mindful of the big picture
- Can work independently and efficiently to meet aggressive timelines where needed
- Adapt to rapidly changing priorities
Qualifications and Experience Required:
- A Master’s degree in quantitative science (statistics [preferred], mathematics, economics, computer science, engineering) with a strong focus on the application of data science to healthcare data with 5+ years of hands-on programming experience; or a Bachelor’s degree in a quantitative field with 10+ years of hands-on programming and analytic experience using healthcare data.
- Must have hands-on RWD/RWE experience with EHR data sources and expert skills in manipulating very large data (trillions of records) at scale
- Must be proactive, curious, and able to navigate through ambiguities and thrive in a setting where we evaluate new data and develop fit-for-purpose approaches
- Advanced programming capacity in R or Python and SQL. SAS is a plus
- Proficiency with common statistical methods and data science methods
- Familiarity with various observational study designs, such as cohort, case-control, cross-sectional
- Ability to effectively communicate methods and findings
- Knowledge of visualization software is a plus
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