Key Responsibilities:

Patient Analytics & Strategy:

- Conduct claims-based analytics to identify treatment pathways, gaps in care, and switching patterns across therapeutic areas

- Develop and apply business rules to create patient cohorts for specific use cases (e.g., newly diagnosed, first-line switchers, persistent patients)

- Analyze adherence and persistency trends using medical and pharmacy claims data

- Perform patient journey mapping to understand diagnosis-to-treatment timelines, therapy progression, and abandonment

- Support unmet need analysis and treatment drop-off mapping across lines of therapy

Real-World Data (RWD) Execution:

- Extract and analyze longitudinal claims datasets (e.g., IQVIA, Symphony, Komodo, DRG)

- Clean and validate raw datasets to build patient-level views that are accurate and research-ready

- Apply inclusion/exclusion criteria, diagnosis/procedure code logic, and other rules for advanced cohort creation

- Generate structured outputs (tables, KPIs, dashboards) that drive decision-making across commercial and medical teams

Business Impact & Commercial Use Cases:

- Translate analytical insights into actionable recommendations for patient acquisition, retention, and education strategies

- Support brand and marketing teams with insights into real-world therapy usage and potential patient activation opportunities

- Contribute to go-to-market strategies by identifying viable patient segments and underserved populations

- Enable omnichannel campaign planning with patient persona development and journey insights

Client Engagement:

- Collaborate with pharma clients to understand key business questions and translate them into analytical approaches

- Present results in a clear and concise manner, emphasizing implications for marketing, access, and field strategy

- Build client trust through responsiveness, domain understanding, and high-quality deliverables

Project Management & Collaboration:

- Manage multiple ongoing patient analytics projects and prioritize tasks effectively

- Work cross-functionally with data science, medical, commercial, and strategy teams to ensure project success

- Contribute to the development of standardized frameworks and reusable code libraries for patient analytics

Required Qualifications:

Education & Experience:

- Graduate/Master's degree from Tier-I/Tier-II institution/university with a relevant concentration (e.g. computer science, statistics) with a strong academic record. Degree in Public Health, Health Economics, Data Science, Pharmacy, or related quantitative fields will be preferred

- Hands-on experience in patient-level analytics, preferably in life sciences consulting, healthcare analytics, or biopharma

- Prior work with large claims datasets (e.g., IQVIA, Symphony, Komodo, Optum) and patient-level longitudinal analysis

- Experience developing cohort definitions, patient selection logic, and real-world evidence use cases