Data Scientist Pharma Commercial Analytics & GenAI

We are seeking a highly motivated Data Scientist to join a Global Data & Digital Innovation (GDDI) team within the pharmaceutical commercial domain. This role will focus on developing AI and machine learning solutions that drive commercial effectiveness, improve HCP engagement, and generate actionable business insights., * Develop and deploy predictive models for patient events, including therapy initiation, adherence, and line-switch prediction.

• Design and scale Next Best Action (NBA) solutions to optimize HCP engagement strategies.
• Build advanced machine learning models using regression, classification, and NLP techniques.
• Develop customer journey analytics and multi-touch attribution models.
• Integrate GenAI capabilities into commercial workflows, including:
• HCP engagement planning
• Content personalization
• AI-powered decision support systems
• GenAI interfaces for ML solutions
• Build and maintain end-to-end ML pipelines, including data ingestion, feature engineering, model training, deployment, monitoring, and retraining.
• Implement MLOps best practices, CI/CD processes, and model governance.
• Partner with Sales, Marketing, Commercial Analytics, and Data Engineering teams to translate business needs into scalable analytical solutions.
• Present insights and recommendations to business stakeholders and leadership., * Databricks
• AWS SageMaker
• Azure ML
• Power BI
• Tableau
• LangChain
• AutoGen

What Success Looks Like

• Delivering scalable AI/ML and GenAI solutions that improve commercial decision-making.
• Driving measurable business impact through advanced analytics and AI innovation.
• Becoming a trusted partner to commercial, analytics, and technology stakeholders.

The ideal candidate combines strong data science expertise with hands-on experience in GenAI, machine learning, and commercial pharmaceutical analytics., * Master’s or PhD in Data Science, Computer Science, Statistics, Mathematics, Operations Research, or a related quantitative discipline.

• 5+ years of Data Science, Machine Learning, or Advanced Analytics experience (or 3+ years with a PhD).
• Strong proficiency in Python and SQL.
• Experience with machine learning techniques including predictive modeling, classification, regression, clustering, and NLP.
• Experience working with healthcare datasets such as Claims, EHR/EMR, CRM, and digital engagement data.
• Knowledge of pharmaceutical or healthcare commercial analytics.

GenAI & AI Requirements

• Hands-on experience with:
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI Agent frameworks such as LangChain, AutoGen, MCP, or A2A
• Familiarity with vector databases, embeddings, and API-based AI integrations.

ML Engineering & MLOps

• Experience with Databricks, AWS SageMaker, Azure ML, or similar platforms.
• Knowledge of model deployment, monitoring, Docker, REST APIs, and CI/CD pipelines.
• Experience building scalable production-grade ML solutions.

Preferred Experience

• Pharmaceutical commercial analytics.
• Patient journey analytics.
• HCP targeting and segmentation.
• Omnichannel marketing analytics.
• Sales force effectiveness.
• Next Best Action (NBA) frameworks.
• Promotional response modeling and multi-touch attribution.