Career Opportunity: Data Scientist (Pharma & Healthcare Analytics)

Experience: 4 – 6 Years

Location: Global Delivery Centres / Remote-Hybrid

Sector: Life Sciences & Healthcare

Education: Bachelor’s or Master’s in CS, Statistics, or Data Science

About the Company: Shaping the Future of Health

We are a global leader in healthcare consulting and technology, dedicated to solving the most complex challenges in the pharmaceutical industry. By blending scientific curiosity with technical depth, we help our clients move from data to decisions, delivering measurable impact across commercial, clinical, and operational landscapes.

The Role: Data Scientist

As a Data Scientist, you will play a key role in delivering end-to-end data science solutions. You will translate ambiguous healthcare business problems into rigorous analytical frameworks, developing scalable machine learning models that improve patient outcomes and drive market strategy.

Key Responsibilities & Technical Execution

• End-to-End Solutioning: Own the lifecycle of data science projects, from initial problem definition to final deployment.

• Advanced Modeling: Build and tune supervised models (classification, regression, uplift), unsupervised techniques (clustering, GMM), and Transformer models.

• Scientific Frameworks: Apply hypothesis testing, Causal Inference, and Survival Analysis to clinical and commercial datasets.

• Data Synthesis: Extract insights from diverse healthcare sources, including Claims, Prescription (LAAD), Lab, and EMR data.

• Production-Ready Engineering: Adhere to best practices in version control and modular code design to build scalable pipelines.

• Strategic Advisory: Present structured, actionable narratives to HCPs, market experts, and client stakeholders.

Required Technical Skills

• Programming: Hands-on mastery of Python, PySpark, and SQL for handling massive healthcare datasets.

• Machine Learning: Strong foundation in feature engineering, model tuning, and evaluation.

• Visualization: Proficiency in Power BI, Tableau, or RShiny to communicate complex results.

• Pharma Domain: (Preferred) Familiarity with structured data like LAAD and unstructured physician notes or publications.

• Cloud & MLOps: (Preferred) Experience with Databricks, AWS/Azure, and tools like MLflow, Docker, or Airflow.

Why Join Our Data Science Team?

• Global Impact: Work on engagements that directly affect patient care and global health markets.

• Technical Growth: Access to cutting-edge accelerators and internal ML assets.

• Collaboration: Partner with world-class domain experts in an environment that values scientific rigor and business acumen.

How to Apply

Are you ready to use data to change the world of healthcare?

👉 Apply via our Careers Portal

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