Product Manager – Data Science
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Job Description
Product Manager building data science workflows, AI agents, and MLOps tools for Fundamental’s NEXUS enterprise AI platform. Owning roadmap, discovery, and product delivery for data science practitioners.
Responsibilities:
- Own and lead the roadmap and product decisions for data science products, from customer discovery through product definition, launch, and iteration
- Work directly with data scientists to understand their needs and usage patterns
- Shape AI agents and data science tools across the platform, making common workflows intuitive while preserving flexibility for technical users
- Define how users guide agents, inspect their work, and understand results, balancing automation with transparency and control
- Own MLOps workflows for managing and monitoring predictive quality of customer models in production
- Turn NEXUS capabilities into coherent user experiences with clear product requirements and practical tradeoffs
- Define success measures for usability, adoption, and customer outcomes; use data, feedback, and product evidence to guide priorities
- Collaborate with engineering, Applied AI/FDEs, product design, and research teams
Requirements:
- 4+ years of experience owning and shipping ML or data science products with an engineering team, from discovery and roadmap decisions through delivery and iteration
- 2+ years hands-on expertise in data science, demonstrating a solid grasp of core workflows including classification, regression, and time series analysis
- Experience working with structured or tabular data and predictive ML workflows
- Experience building agentic products, with practical understanding of their limitations and the interaction patterns that help users trust and control them
- Strong customer discovery skills: uncover the problem behind a request, test assumptions and translate learnings into product decisions
- Technical fluency and strong collaboration with engineers and applied data scientists, with the ability to turn ambiguity into a clear, deliverable scope
- Data-driven prioritization grounded in usage data, evaluation results, and user evidence
- Nice to have: earlier client-facing data science experience followed by product ownership with an engineering team
- Nice to have: experience building internal data science tools for Applied AI, solutions teams, or technical customer-facing teams
- Nice to have: experience in an early-stage AI company with enterprise customer or forward-deployed exposure
Benefits:
- Competitive compensation with salary and equity
- Comprehensive health coverage for you and your dependents
- Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
- Relocation support for employees moving to join the team in one of our office locations
- A high-trust, low-ego culture that values diversity of thought, ownership and initiative, with respect for personal boundaries and working styles
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