Geospatial Data Product Manager — Maps & AI

Socket.dev; Mountain View (CA); On-site; USD 138,000 - 197,000; Full time

Job summary

Socket.dev is seeking a Data Product Manager to guide basemap data products from conception to launch, collaborating with engineering and operations to scale AI-powered mapping data pipelines for maps and geospatial applications.

You will define enterprise-grade quality standards, identify new data sources, and lead cross-functional teams while balancing business impact and technical feasibility; prior ML deployment and geospatial experience are highly valued.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 3 years of experience in product management or related technical role.
• 1 year of experience taking technical products from conception to launch.

Responsibilities

• Collaborate with engineering and operations to deliver scalable systems powered by AI and data that power maps and geospatial applications.
• Define enterprise-grade quality standards for core basemap data products, ensuring we meet enterprise needs in AI-powered services.
• Identify and integrate new data sources, such as vehicle sensor observations, driving telemetry, user reports, and imagery to maintain a fresh map of the real world.
• Drive the prioritization and development of new features that increase detail of our foundational roads and speed limit data.
• Lead market research on both consumer and auto offerings to influence the data roadmap.

Skills

Product management experience

End-to-end product development

Executive presentation

ML model deployment

Geospatial data

Cross-functional leadership

SQL

Python

Data analysis

Education

Bachelor's degree or equivalent practical experience

Job description

Socket.dev is seeking a Data Product Manager to guide basemap data products from conception to launch, collaborating with engineering and operations to scale AI-powered mapping data pipelines for maps and geospatial applications.

You will define enterprise-grade quality standards, identify new data sources, and lead cross-functional teams while balancing business impact and technical feasibility; prior ML deployment and geospatial experience are highly valued.