Product Manager – Data Science

This is a fully remote position, open to applicants in Europe.

📋 Description

• Take charge of the roadmap and product decisions for data science products, overseeing everything from customer discovery to product definition, launch, and iteration.

• Collaborate closely with data scientists to comprehend their needs and usage patterns.

• Design AI agents and data science tools across the platform, ensuring that common workflows are user-friendly while maintaining flexibility for technical users.

• Establish how users interact with agents, evaluate their outputs, and interpret results, ensuring a balance between automation, transparency, and control.

• Manage MLOps workflows to oversee and monitor the predictive quality of customer models in a production environment.

• Transform NEXUS capabilities into cohesive user experiences by defining clear product requirements and making practical trade-offs.

• Set success metrics for usability, adoption, and customer outcomes; utilize data, feedback, and product evidence to inform priorities.

• Work in partnership with engineering, Applied AI/FDEs, product design, and research teams.

⛳️ Requirements

• A minimum of 4 years of experience managing and delivering ML or data science products in conjunction with an engineering team, spanning from discovery and roadmap planning to delivery and iteration.

• At least 2 years of hands-on experience in data science, showcasing a robust understanding of fundamental workflows such as classification, regression, and time series analysis.

• Proficiency in working with structured or tabular data and predictive ML workflows.

• Experience in developing agentic products, with a practical understanding of their limitations and the interaction patterns that foster user trust and control.

• Strong skills in customer discovery: identifying the underlying problem behind requests, testing assumptions, and translating insights into product decisions.

• Technical fluency with excellent collaboration skills with engineers and applied data scientists, capable of converting ambiguity into a clear, actionable scope.

• Data-driven prioritization based on usage data, evaluation results, and user feedback.

• Nice to have: prior client-facing data science experience followed by product ownership with an engineering team.

• Nice to have: experience in creating 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 exposure to enterprise customers or forward-deployed environments.

🏝️ Benefits

• Competitive compensation package including salary and equity.

• Comprehensive health insurance coverage for you and your dependents.

• Paid parental leave for all new parents, including those on adoptive and surrogate journeys.

• Relocation assistance for employees moving to join the team in one of our office locations.

• A high-trust, low-ego culture that emphasizes diverse perspectives, ownership, and initiative, while respecting personal boundaries and varying working styles.