Senior Data Scientist

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 data analytics. The ideal candidate will combine deep clinical understanding, strong patient-level data expertise, and advanced analytical skills to generate insights that drive strategic and operational decisions. This role requires hands-on experience with integrated healthcare datasets (claims, EHR, lab, pharmacy) and the ability to translate complex 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