Define and own the Data & AI product strategy and roadmap for the S&M + GM pod by deeply partnering with business leaders to proactively identify high-impact opportunities, shape problem definitions, and drive aligned priorities.
Translate ambiguous business problems into clear product direction and measurable outcomes.
Be hands-on with data: query datasets, review schemas, and validate assumptions through analysis.
Lead end-to-end product discovery with interviews, workflow mapping, data assessments, ROI modeling, etc.
Define clear product requirements (PRDs, user stories, acceptance criteria) and success metrics.
Design and run experiments to validate product performance and measure causal impact.
Partner with data and AI/ML engineering resources to deliver scalable products and capabilities.
Guide development of robust data pipelines and unified data models.
Own the end-to-end ML lifecycle: feature definition, evaluation, deployment, monitoring, drift detection, and retraining.
Ensure training–serving consistency, model versioning, and clear deployment decision gates.
Define and implement AI product patterns, including agentic workflows and RAG.
Champion data quality, lineage, and reliability through data contracts and observability standards.
Partner with governance teams (Security, Legal, Compliance, AI Governance) to operationalize AI responsibly.
Launch products with supporting enablement activities to ensure solutions are embedded in workflows with confidence.

Requirements

7–10+ years of product management experience, including 3+ years building data products, AI/ML systems, or related platforms.
Demonstrated domain fluency in Sales, Marketing, Field Medical, and/or related commercial/GTM functions.
Strong understanding of sales funnel, marketing funnel, medical affairs funnel, and related funnels to relate product ideas to the overall opportunity landscape.
Familiarity with key domain-relevant tooling (e.g., Salesforce) and associated data.
Strong technical acumen (e.g., querying data, working in notebooks for EDA and experimentation, modeling datasets).
ML/MLOps literacy (evaluation metrics, experimentation, feature stores, CI/CD, monitoring, drift).
Experience shipping LLM-powered or AI products (prompting, RAG, evaluation frameworks, guardrails).
Familiarity with modern data stacks (e.g., Snowflake, dbt, AWS/SageMaker, Airflow/Dagster).
Strong stakeholder leadership and communication skills, with the ability to work across technical and business teams.
Experience working in regulated environments (e.g., healthcare, life sciences, fintech).

Benefits

Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents.
Free testing for employees and their immediate families.
Fertility care benefits.
Pregnancy and baby bonding leave.
401k benefits.
Commuter benefits.
Generous employee referral program.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data product managementAI/ML systemsdata analysisproduct requirements definitionML lifecycle managementdata pipeline developmentexperiment designdata modelingquerying dataevaluation metrics

Soft Skills

stakeholder leadershipcommunication skillsproblem definitionprioritizationcollaborationanalytical thinkingstrategic thinkingadaptabilityinfluencecross-functional teamwork