Core Responsibilities

Patient-Level Analytics & Insights

- Lead patient journey analytics using longitudinal patient-level healthcare data (claims, EMR, pharmacy, lab) to build robust analytical solutions for pharma clients.
- Perform treatment pattern analysis, disease progression studies, and patient segmentation to identify high-value populations and optimize targeting strategies.
- Translate complex APLD datasets into transparent, actionable business insights for sales, marketing, and market access teams.

Advanced Analytics & Modeling

- Design and implement scalable, compliant data analysis solutions using statistical modeling, machine learning, and commercial analytics techniques
- Build, validate, and operationalize predictive models, pipelines, and dashboards for patient identification, HCP segmentation, and promotional optimization
- Apply and evaluate statistical/ML techniques relevant to pharma analytics (e.g., MMM, Test & Control, OCE analytics, budget optimization); compare methods for fit, accuracy, and interpretability

Solution Architecture & Delivery

- Support planning and day-to-day execution of Decision Sciences projects, owning defined workstreams and deliverables from problem framing through insight delivery
- Lead end-to-end data analysis: querying data, interpreting and transforming it, and creating insights visualized in charts/dashboards for business audiences
- Collaborate with business and IT stakeholders to align analytical approach with strategic goals and ensure data governance, accuracy, and timeliness.

Stakeholder Engagement & Influence

- Partner with cross-functional teams (commercial,



digital, medical, access, NPP) to clarify objectives, scope, timelines, and resource needs; maintain project trackers and documentation
- Present recommendations that build investment, targeting, and channel strategy; communicate implications and next-best actions to senior leadership
- Drive adoption of analytics capabilities by embedding insights where decisions happen and measuring impact to scale what delivers competitive advantage

Required Skills & Experience Education Bachelor's in Statistics, Data Science, Engineering, or related quantitative field; Master's/MBA preferred

Experience58 years in pharma/life sciences analytics with 2+ years in APLD or patient-level data; 3+ years in analytics/decision sciences with 2+ years in PharmaTech domain

Technical SkillsSQL (required), Python/R, PySpark; advanced Excel; Tableau/Power BI; experience with commercial analytics tools (Market Mix Modeling, Test & Control, OCE analytics)

Data ExpertisePatient-level datasets (claims, EMR, specialty pharmacy, lab); US pharma commercial data; omnichannel marketing measurement; HCP segmentation

Soft SkillsStrong communication to influence senior decision-makers; ability to work in agile, client-facing settings; stakeholder engagement and project management

Typical Tools & Platforms

- Data Sources: Claims (IQVIA, Komodo, Truven), EMR (Optum, Flatiron), Specialty Pharmacy, Lab Data, CRM (Salesforce, Veeva)
- Analytics Platforms: Databricks, Snowflake, Delta Lake, SAP, Model N
- Visualization: Tableau, Power BI, MicroStrategy, Qlik
- Programming: SQL, Python, R, PySpark, SAS

📌 Consultant - APLD (Hyderabad)
🏢 CHRYSELYS
📍 Hyderabad