Role Overview

- Support pharma/biopharma client projects by transforming APLD, formulary, coverage, and healthcare datasets into actionable market access insights.

- Analyze payer, IDN, GPO, PBM, and coverage data to support access strategy, pull-through execution, and account planning.

- Build data pipelines and BI reports using Data Lake architecture and multiple integrated datasets.

- Perform data integration, harmonization, transformation, and univariate/multivariate analysis.

Key Responsibilities

- Ingest, clean, and harmonize anonymized patient-level data to analyze treatment journeys, adherence, persistence, switching, and access barriers.

- Integrate MMIT formulary data, including coverage status, prior authorization, restrictions, step edits, and covered lives.

- Develop payer and channel scorecards across lines of business and geographies.

- Build IDN and GPO opportunity maps to identify influence pathways, member alignment, and contracting opportunities.

- Analyze coverage differences across Commercial, Medicare, and Medicaid segments.

- Prepare executive summaries, pre-reads, presentations, and data-driven recommendations for clients.





- Identify appropriate datasets for new business requests and develop SQL queries and analytical outputs.

- Translate complex data into clear, decision-oriented business insights.

- Understand client business requirements, data, operating rules, and standard operating procedures.

Required Skills

- 3 5 years of experience working with pharmaceutical/biotechnology datasets such as Claims, Payer Coverage, and secondary healthcare data.

- Solid experience in data processing, profiling, cleansing, standardization, and integration.

- Advanced SQL and analytical skills.

- Experience with Data Lake / cloud data environments.

- Hands-on experience with Python / Jupyter Notebooks / SageMaker.

- Experience with BI tools such as Tableau, Power BI, Qlik, or QuickSight.

- Strong data visualization and data storytelling skills.

- Ability to perform univariate and multivariate analysis.

- Strong problem-solving and analytical capabilities.

- Ability to work independently and collaborate effectively with teams and clients.

Preferred Education

- Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Econometrics, Engineering, Finance, Management Science, or another quantitative discipline.

📌 Senior Associate - Market Access (Hyderabad)
🏢 Three Across
📍 Hyderabad