AI and Data Science Product Manager

Job Description

We are seeking an experienced Data Scientist, AI/ML Engineer, or AI Product Manager with a passion for Product Management to join our AI capability engineering team. This role is ideal for someone who has demonstrated strong analytical or AI/ML fundamentals and is eager to expand their scope into product ownership of our NLP and Generative AI products. The focus is turning ML, LLM, and Agentic AI prototypes into reliable, maintainable services that enable insights from unstructured and semi-structured data from across our company’s research and development pipeline.

You'll be mentored by a senior product manager and work directly alongside other data scientists, developers, and scientific subject matter experts. You'll gain hands-on exposure to large language model (LLM) systems, see your work accelerate research, and ultimately help bring therapeutics to patients. As you grow, you'll have opportunities to expand your skills by owning one or more products, including leading product discovery, requirements gathering, stakeholder engagement, and adoption. The position is embedded within a cross-disciplinary team of data scientists, bioinformaticians, and engineers dedicated to using cutting-edge AI/ML and data science techniques to drive drug discovery and development.

Primary Responsibilities:

• Product Discovery & Stakeholder Alignment: Partner with business partners and scientists to understand operational pain points, uncover high-value opportunities, and translate ambiguous needs into technical user stories.
• Backlog & Roadmap Prioritization: Own and prioritize your product’s backlog and organize it for regular deliveries.
• Requirement Specifications: Author clear requirements, acceptance criteria, and value capture plans to ensure that technical teams and business stakeholders share a unified definition of success.
• Adoption & Change Management: Connect with users - demo features, lead user enablement sessions, gather structured feedback, and measure adoption metrics to drive continuous product refinement.
• Exploratory Data Analysis: Understand our partners’ structured and unstructured data and how it can be used to address their needs
• Pipeline Integration: Collaborate with Data Engineering teammates to integrate data science prototypes into reliable, production-ready pipelines, adhering to software engineering best practices.
• Validation: Establish clear evaluation metrics and confirm sufficient performance for the business need.

Preferred Qualifications:

• Technical Foundations: Strong proficiency in Python, SQL, git, and data manipulation libraries (e.g., Pandas).
• Model Evaluation & Validation: Demonstrated experience establishing model evaluation frameworks (e.g., defining LLM benchmarks, measuring precision/recall for NLP tasks) to ensure business viability.
• NLP and Agentic AI Exposure: Hands-on experience or academic familiarity with NLP techniques, (e.g., Hugging Face, spaCy, LangChain) to parse unstructured or semi-structured data and to Agentic AI frameworks such as LangGraph.
• Familiarity with LLM and Agentic AI Architectures & Techniques: Practical exposure to Large Language Model (LLM) workflows, including Retrieval-Augmented Generation (RAG), prompt engineering, and fine-tuning paradigms.
• Eagerness to transition into product management, with prior exposure to drafting technical requirements, defining success metrics, or structuring user stories.
• Exceptional ability to translate complex data science concepts to cross-functional stakeholders and an eagerness to acquire domain knowledge.
• Familiarity with AI Coding Assistants a plus.
• A Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Biomedical Informatics, Engineering, or a related technical field, or equivalent practical experience.

Minimum Requirements:

• 3+ years of professional experience in data science, AI/ML Engineering, Agentic AI, AI Product Management, or related discipline.
• HS diploma

Required Skills:

Asset Management, Asset Management, Benefits Management, Biomedical Informatics, Computer Science, Data Domain, Data Engineering, Data Science, Exploratory Analysis, Generative AI, LangGraph, Large Language Models (LLMs), Management System Development, Pandas Python Library, Product Adoption, Product Discovery, Product Improvements, Product Management, Product Ownership, Prompt Engineering, Requirements Management, Retrieval-Augmented Generation, Stakeholder Relationship Management, Strategic Planning, System Designs {+ 1 more}

Preferred Skills:

Current Employees apply HERE

Current Contingent Workers apply HERE

US and Puerto Rico Residents Only:

Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process.

…