Data Scientist

Job Title: Data Scientist - Pharmaceutical Commercial Analytics & Streategy

Duration: 12 Months Contract (Extendable)

Position Summary

We are seeking a highly motivated Data Scientist to join a top-tier pharmaceutical client's Global Data & Digital Innovation (GDDI) organization. This role bridges advanced machine learning, GenAI agent development, and production-grade MLOps pipelines to deliver actionable insights across Sales, Marketing, and Advanced Analytics teams.

Domain Expertise Required : This role focuses entirely on the Pharmaceutical Commercial Domain, combining advanced machine learning, GenAI agent development, and production-grade MLOps pipelines to drive commercial effectiveness across Sales, Marketing, and Advanced Analytics.

Key Responsibilities

Core Data Science & Commercial Strategy

• Predictive Modeling: Develop and deploy models for patient events (line switches, initiation) and patient journey/longitudinal data analysis.
• Next Best Action (NBA): Scale NBA solutions to optimize multichannel HCP engagement and segmentation.
• Advanced ML: Apply regression, classification, and NLP techniques for commercial effectiveness.
• Marketing Analytics: Create multi-touch attribution pipelines for customer journeys and promotional response modeling.
• Stakeholder Support: Partner with Sales, Marketing, and Analytics teams to translate complex business problems into analytical solutions.

GenAI Integration

• Integrate GenAI capabilities into commercial workflows (HCP engagement planning, content personalization, and GenAI interfaces for ML pipelines).

ML Engineering & MLOps

• End-to-End Pipelines: Oversee build/maintenance of pipelines (data ingestion, feature engineering, training, evaluation, and deployment).
• MLOps Best Practices: Implement model versioning, monitoring, retraining, and CI/CD integration.
• Data Platforms: Work with large-scale healthcare datasets (Claims, EHR/EMR, CRM, digital engagement data) ensuring HIPAA compliance.

Required Qualifications

Education & Experience

• Master’s Degree with 5-7+ years of experience OR PhD with 3-5+ years of experience.
• Degree must be in Data Science, Computer Science, Statistics, Operations Research, Mathematics, or a related quantitative discipline.
• Experience must be in data science, machine learning, or advanced analytics.
• Preferred: Pharmaceutical/life sciences commercial analytics or healthcare consulting experience.

Technical Skills & Stack

• Core DS: Python (preferred) or R; SQL; Supervised/Unsupervised ML algorithms; Statistical analysis and experimental design.
• GenAI Stack: Hands-on experience with LLMs, Prompt Engineering, RAG architecture, and Agent-based AI systems (LangChain, MCP, A2A, AutoGen). Familiarity with Vector databases, embeddings, and API integrations.
• MLOps & Infra: Experience with pipeline deployment and monitoring using Databricks, Azure ML, or AWS SageMaker. Knowledge of REST APIs, containerization (Docker), and CI/CD pipelines.
• Visualization: Ability to build demo apps in Databricks; proficiency with BI tools (Power BI, Tableau); strong storytelling skills.