Senior Data Scientist
Overview
DataZymes is seeking a highly analytical Data Scientist with 4-7 years of experience in patient-level data to generate insights that drive strategic and operational decisions. The role requires deep clinical understanding, hands-on healthcare data expertise, and the ability to translate complex analyses into actionable business recommendations.
What You'll Do7
- 1Apply strong understanding of healthcare delivery models and patient care pathways
- 2Conduct patient-centric analysis including treatment pattern, line-of-therapy, and disease progression analyses
- 3Integrate and analyze claims, EHR, lab, and pharmacy datasets to develop longitudinal patient journeys across multiple care settings
- 4Develop risk stratification models using machine learning techniques to prioritize patients based on clinical and behavioral risk factors
- 5Apply time-series and survival analysis to study treatment duration, drop-offs, and patient retention trends
- 6Leverage NLP on patient interaction data (notes, call logs) to identify common barriers like side effects, cost issues, and therapy fatigue
- 7Translate analytical findings into clear, strategic insights and develop executive-ready presentations and dashboards
Requirements8
- 14+ years of experience as an analytics consultant with at least 2 years in the pharma domain
- 2Hands-on experience with patient-level datasets (claims, EHR, lab, pharmacy data)
- 3Experience with patient journey analysis, treatment patterns, disease progression, and advanced analytics
- 4Proficiency in SQL and Python for predictive modeling (regression, classification, clustering)
- 5Experience combining multiple healthcare datasets and building longitudinal patient views
- 6Ability to translate complex analysis into actionable business/clinical insights
- 7Experience with time-series analysis and/or survival analysis for studying treatment duration, patient drop-off, or retention trends
- 8Experience building risk stratification models using ML techniques to prioritize patients based on clinical or behavioral risk factors
Who Should Apply
An experienced data scientist with a strong background in pharma analytics, skilled in patient-level data integration, predictive modeling, and advanced analytical techniques such as time-series, survival analysis, and NLP. The ideal candidate is client-focused, able to translate complex data into actionable insights, and adept at handling large healthcare datasets.
Salary Insight
Open to discussion; CTC includes 10% variable component (from mandatory note).
Required Skills
Application Tip
Highlight your experience with patient-level datasets and specific projects in treatment pattern analysis or risk stratification in your resume and cover letter.