Data Scientist/ Architect

• Develop and deploy predictive models for patient events (line switches, initiation)
• Scale Next Best Action (NBA) solutions to optimize HCP engagement strategies across channels to various products
• Apply advanced ML techniques including regression, classification, and NLP techniques
• Create multi touch attribution pipelines for the customer journeys and optimization
• Integrate GenAI capabilities into commercial workflows such as:
• HCP engagement planning
• Content personalization
• Gen AI interfaces for ML pipelines

ML Engineering & Pipeline Development

• Oversee build and maintenance of end-to-end ML pipelines including:
• Data ingestion, feature engineering, model training, evaluation, and deployment
• Implement MLOps best practices:
• Model versioning, monitoring, and retraining pipelines
• CI/CD integration for scalable deployment
• Work with modern data platforms (e.g., Databricks, AWS)

Commercial Strategy & Stakeholder Support

• Partner with Sales, Marketing, and Sales Analytics teams to translate business problems into analytical solutions
• Deliver actionable insights and recommendations to senior stakeholders
• Collaborate with:
• Advanced Analytics teams (modeling and experimentation on alerts)
• Data Engineering teams (data pipelines and infrastructure)
• Business stakeholders (Sales, Marketing, Market Access)
• Act as a bridge between technical and business teams, ensuring adoption of advanced analytics and AI solutions

Data Management & Compliance

• Work with large-scale healthcare datasets such as:
• Claims, EHR/EMR, CRM, and digital engagement data
• Ensure compliance with data privacy and regulatory standards (e.g., HIPAA)

We are seeking a highly motivated Data Scientist to join the Global Data & Digital Innovation (GDDI) organization within the pharmaceutical commercial domain. This role focuses on building data science and AI-driven solutions, including predictive patient event modeling, Next Best Action (NBA) engines for HCP engagement, and GenAI-powered decision agents to enhance commercial effectiveness.

The ideal candidate will combine strong machine learning expertise with experience in GenAI agent development and scalable ML pipelines, enabling actionable insights for stakeholders across GDDI, Sales, Marketing, Sales Analytics, and Advanced Analytics functions., * Master's or PhD in:

• Data Science
• Computer Science
• Statistics
• Operations Research
• Mathematics or a related quantitative discipline

Experience

• 5-7+ years (Master's) or 3-5+ years (PhD) in:
• Data science, machine learning, or advanced analytics
• Pharmaceutical / life sciences commercial analytics preferred
• Healthcare analytics or consulting experience

Technical Skills

Core Data Science

• Proficiency in:
• Python (preferred) or R
• SQL
• Strong understanding of:
• Machine learning algorithms (supervised/unsupervised learning)
• Statistical analysis and experimental design

GenAI & Modern AI Stack

• Hands-on experience with:
• Large Language Models (LLMs) and GenAI frameworks
• Prompt engineering and RAG architecture
• Agent-based AI systems (e.g., LangChain, MCP, A2A, AutoGen)
• Familiarity with:
• Vector databases and embeddings
• API-based AI integrations

ML Engineering / MLOps

• Experience with:
• Overseeing ML pipelines (training * deployment * monitoring)
• Tools such as Databricks, Azure ML, AWS SageMaker
• Knowledge of:
• Model deployment, REST APIs, containerization (Docker)
• CI/CD pipelines for ML systems

Visualization & Communication

• Ability to build apps for demo purposes using Databricks
• Experience with BI tools (Power BI, Tableau)
• Strong storytelling skills to communicate insights effectively

Domain Expertise (Preferred)

• Pharmaceutical commercial domain experience, including:
• Patient journey and longitudinal data analysis
• HCP targeting and segmentation
• Omnichannel marketing analytics and campaign optimization
• Experience in:
• Next Best Action (NBA) frameworks
• Sales force effectiveness
• Promotional response modeling especially Multi- touch Attribution

Key Competencies

• Strong problem-solving mindset with business acumen
• Ability to bridge AI innovation with commercial impact
• Excellent stakeholder management and communication skills
• Experience working in cross-functional, global teams
• High attention to detail and commitment to quality