Remote Product Manager: Education Knowledge Graph & Data

Remote; San Francisco (CA); On-site; USD 190,000 - 238,000; Full time

Benefits offered by this job

401(k) match

Volunteer time off

Family-forming benefits funding

Relocation support

Job summary

Learning Commons seeks a Product Manager for a 12-month fixed-term role to build the data layer for AI in education. You’ll own datasets end-to-end, collaborate with engineers and partners, and shape APIs and data model decisions that power classroom-ready tools grounded in learning science.

You’ll work hands-on with data, plan near- and long-term roadmaps, and coordinate across engineering, partnerships, and marketing to ship impactful data products for schools.

Qualifications

• 3–5 years of product management experience with a track record of shipping, preferably data products, APIs, or developer-facing platforms.
• Education or edtech grounding — You've built products in education or worked in the field, and you understand how curricula, academic standards, and classrooms work well enough to judge what developers serving schools actually need.
• Works well with deep technical experts — You partner with engineers and data experts as a credible peer: you ask sharp questions, pressure-test tradeoffs, and write up complex technical decisions clearly enough for developers to build on.
• Hands-on data fluency and modeling judgment — You personally open raw data files (JSONL, CSV), write queries (SQL, Cypher, or similar), and pull your own counts rather than delegating the check; you can reason about entities and relationships, sketch the nodes and edges for a new dataset, and tell a data gap from a modeling gap.
• Strong product sense — You understand what the people building on your product are trying to do and where they get stuck, and turn that into priorities.]
• job_responsibilities_description ["Own datasets end to end — Take each dataset from acquisition and licensing through modeling, ingestion, and launch. Write the product docs that define the work clearly enough for engineering to build and ship without rework.","Partner with our users — Work closely with the developers and build partners who use the graph to understand their needs and where they get stuck, and spot opportunities for the graph to solve those problems. Help shape the API surfaces they build on, across the REST API and beyond.","Plan the work, short and long term — Use partner evidence to shape the roadmap — which data to bring in and how it should grow — and plan the near-term work with engineering so the team ships against a clear, current plan.","Work hands-on in the data — Open the source data yourself, run coverage and gap analyses, and verify what ships against the source. Decide how a new source maps onto the graph, when to reuse the model and when to extend it, and
• CoT_job_summary_shortcommabantmeasures?

Responsibilities

• Own datasets end to end — Take each dataset from acquisition and licensing through modeling, ingestion, and launch. Write the product docs that define the work clearly enough for engineering to build and ship without rework.
• Partner with our users — Work closely with the developers and build partners who use the graph to understand their needs and where they get stuck, and spot opportunities for the graph to solve those problems. Help shape the API surfaces they build on, across the REST API and beyond.
• Plan the work, short and long term — Use partner evidence to shape the roadmap — which data to bring in and how it should grow — and plan the near-term work with engineering so the team ships against a clear, current plan.
• Work hands-on in the data — Open the source data yourself, run coverage and gap analyses, and verify what ships against the source. Decide how a new source maps onto the graph, when to reuse the model and when to extend it, and set clear, testable acceptance criteria engineers can build against.
• Keep the cross-functional team aligned — Work across engineering, Trust, partnerships, tech writers, and marketing to move each launch forward and keep everyone working from the same plan.

Skills

PM experience

Edtech background

Data fluency

Developer collaboration

Product sense

Education

Education or edtech grounding

Tools

SQL

JSONL/CSV

Job description

Learning Commons seeks a Product Manager for a 12-month fixed-term role to build the data layer for AI in education. You’ll own datasets end-to-end, collaborate with engineers and partners, and shape APIs and data model decisions that power classroom-ready tools grounded in learning science.

You’ll work hands-on with data, plan near- and long-term roadmaps, and coordinate across engineering, partnerships, and marketing to ship impactful data products for schools.