Data Scientist/AI Engineer
The Fountain Group
Fairport, United States of America
18 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Intermediate Compensation
$ 212KJob location
Remote
Fairport, United States of America
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Python
Machine Learning
Power BI
Standard Sql
Azure
Tableau
Large Language Models
Prompt Engineering
Containerization
Core Data
Information Technology
Machine Learning Operations
Api Design
REST
Docker
Unsupervised Learning
Databricks
Job description
- 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.
- A successful candidate will be able to Delivering scalable AI/ML and GenAI solutions that drive commercial insights. Able to enable smarter, real-time decision-making for Sales and Marketing teams.
- Will be responsible for successfully deploying GenAI agents and production-grade ML pipelines
- Becoming a trusted partner within the Global Data & Digital Innovation organization
Requirements
- Master's or PhD in: Data Science,Computer Science, Statistics, Operations Research, Mathematics or a related quantitative discipline
- 5-7+ years (Master's) or 3-5+ years (PhD)
- Core Data Science
- 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, and ML Engineering / MLOps
- Experience Overseeing ML pipelines (training * deployment * monitoring)
- Tools such as Databricks, Azure ML, AWS SageMaker
- Model deployment, REST APIs, containerization (Docker)
- CI/CD pipelines for ML systems
- Ability to build apps for demo purposes using Databricks
- Experience with BI tools (Power BI, Tableau)
- Pharmaceutical commercial domain experience, including: Patient journey and longitudinal data analysis, HCP targeting and segmentation.
- Omnichannel marketing analytics and campaign optimization