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Healthcare Data Scientist
Epic Insurance Brokers and Consultants · Flexible / Remote
Publicada em 29/07/2026
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Pharmaceutical Strategies Group (PSG) relentlessly advocates for clients as they navigate complex and ever-changing drug cost management challenges. Our mission, as we partner together with our clients, is to develop innovative drug management solutions that deliver exceptional insights with financial and clinical value.
PSG, an EPIC Company, is fueled and driven by capable, committed people who share common beliefs and values and “bring it” every day. For over 30 years PSG has been leading the way in pharmacy intelligence and growing as a result. This means we have opportunities for you to join our amazing team of talented individuals!
JOB OVERVIEW:
Artemetrx is PSG’s robust data and analytics platform that drives measurable financial results for clients through advanced healthcare data, reporting, and analytics. The Data Scientist will support the continued evolution of Artemetrx by helping develop, implement, and scale analytical capabilities that improve client decision-making, identify opportunities for cost and utilization management, and support the next generation of AI-enabled drug management tools.
This role is designed for a highly analytical, curious, and technically capable individual who can work with a variety of healthcare data sets, including medical and pharmacy claims data, to uncover insights, build predictive models, and support data-driven solutions. The Data Scientist will partner with clinicians, analysts, consultants, product leaders, and technical teams to translate business questions into analytical approaches, prepare and analyze complex data, and communicate findings clearly to technical and non-technical stakeholders.
LOCATION: Remote - Anywhere in the continental U.S.
WHAT WE’RE LOOKING FOR:
At least 2+ years of healthcare and/or pharmaceutical analytics experience
Strong experience using SQL to write queries
Python or R experience, in particular experience building data analysis, machine learning, or fo
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