Senior Product Manager, Data Products

Description

The Data Products team sets the direction for data at the company. Software work is becoming a shared, interactive activity, and the team is rethinking how people get insights from it.

People and agents should be able to question data in plain conversation and dig deeper, so decisions come faster and hold up better.

The team builds the internal analytics, data science, and experimentation platforms used across the whole company, directly or through agents such as the company's own bot, Claude, and Codex.

You will be the second PM on the team, helping shape how the company builds with and interacts with data.

Candidates may apply for up to 3 roles within 12 months so that efforts are not duplicated.

Responsibilities

• Work with customers, engineers, and data teams to see their workflows and where agents fall short, then find out why.
• Write the strategy and roadmap for your area and define success metrics that set priorities and show where to invest.
• Write requirements and prototype with coding agents alongside engineering and design.
• Keep iterating after launch, since launching is only the start.
• Help the company move toward a data-driven culture by making experiments easier to design, launch, and analyze.
• Bring insights into team channels so people can share and act on data where they already work.
• Work with product teams to turn the best internal tools into features for customers.
• Build the context agents need to find, interpret, and reason over company data accurately.
• Equip agents with tools, MCP servers, and APIs so they can investigate questions, run analyses, and recommend actions within the flow of work.
• Build conversational analytics, dashboards, and notebooks that take teams from a question to an insight.
• Evolve the data platform and pipelines to support more complex analytical work quickly and reliably.

Requirements

• 5+ years shipping technical products as a PM, data scientist, or analyst, with a hand in shaping a product roadmap.
• Background in data science, data engineering, or product analytics.
• Working knowledge of A/B testing and the statistics behind shipping decisions.
• Hands-on experience building working prototypes with coding agents.
• Ability to explain technical tradeoffs clearly to engineers and executives.
• You use coding agents every day, understand the pain points of both data builders and data consumers, and are comfortable digging into details with developers.
• Even better if: you have built agents, MCP servers, or LLM products, including their evals.
• Even better if: you have shipped data or analytics features to external customers.
• Even better if: you have driven adoption of a new tool or practice across an organization.
• Even better if: you know semantic layers or data catalogs such as dbt or DataHub.
• Even better if: you know experimentation platforms such as Statsig, Eppo, or Optimizely.
• Even better if: you know warehouses and query engines such as Snowflake, Trino, or Spark.

Benefits

• Benefits and resources aimed at helping you find balance.
• AI agents that help you have more impact in your work.