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We are looking for passionate and driven professionals to join DataZymes, a next-generation analytics and data science company founded in 2016. At DataZymes, we focus on driving technology-led innovation and helping clients maximize the value of their data and analytics investments through cutting-edge platforms and consulting expertise. If you are excited about working on impactful solutions in the healthcare analytics space and want to be part of a high-performance, fast-growing team, we’d love to hear from you.
DataZymes is seeking a highly analytical and client-focused Senior Data Scientist with 4–7 years of experience in healthcare dataanalytics. The ideal candidate will combine deep clinical understanding, strongpatient-level data expertise, and advanced analytical skills to generateinsights that drive strategic and operational decisions.
This role requires hands-on experience with integratedhealthcare datasets (claims, EHR, lab, pharmacy) and the ability to translatecomplex analyses into clear, actionable business recommendations
Clinical & Therapeutic Analytics:
- Apply strong understanding of healthcare delivery models and patient care pathways
- Conduct patient centric analysis like treatment pattern, line-of-therapy, and disease progression analyses etc.
Patient-Level Data Integration & Journey Mapping
- Integrate and analyze claims, EHR, lab, and pharmacy datasets etc to develop longitudinal patient journeys across multiple care settings
- Define cohorts, enrollment logic, and episode-of-care frameworks
- Ensure data quality, consistency, and reproducibility
Advanced Analytics & Predictive Modeling
- Develop complex SQL /Python queries for large-scale healthcare datasets
- Use Python to perform predictive modelling to build and validate models (classification, regression, survival, clustering etc)
Data Interpretation & Storytelling
- Translate analytical findings into clear, strategic insights and develop executive-ready presentations and dashboards
- Communicate complex methodologies to both technical and non-technical stakeholders
- Quantify business and clinical impact of recommendations
Innovation & Learning Agility
- Quickly ramp up in new therapeutic areas and problem domains
- Test innovative analytical methods and modeling approaches
- Adapt to evolving client priorities and ambiguous problem statements
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