Architect - III

Position: Architect - III*
Job Title:
Data Scientist

Location:
Remote
Duration: 12 Months with possible extension
Pay Rate: $102.19

Overview

• 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.

Key Responsibilities

• 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)

Required Qualifications
Education
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., Lang Chain, MCP, A2A, Auto Gen)

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 Sage Maker

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

What Success Looks Like
Delivering scalable AI/ML and GenAI solutions that drive commercial insights
Enabling smarter, real-time decision-making for Sales and Marketing teams
Successfully deploying GenAI agents and production-grade ML pipelines
Becoming a trusted partner within the Global Data & Digital Innovation organization