Senior Technical Product Manager, Data Acquisition

Responsibilities

• Ensure that GAIA has the customer content and supporting analytical views and tools to achieve its goals for the creation of foundation models requiring this data
• Help realize additional return on GAIA data investments by customizing our datasets, analytical views, and tools for general use within the company, and making those capabilities and DAQ experience and standards (aka DAQ Center of Excellence) generally available in a responsible fashion via our internal platforms
• Identify customer and third party developer workflows that could leverage our analytical capabilities and tools (but, to be clear, not datasets) and influence and partner with non-GAIA PMs to support the delivery of these capabilities to those external parties
• For All Three Groups Of Stakeholders, You Will Be Responsible For Defining Requirements, Overseeing Development Prioritization, Arranging Delivery, And Driving Adoption Of The Products In Your Portfolio, And For Creating And Guiding a Strategy And Roadmap For That Portfolio As a Whole
• In FY27, We Anticipate The Following Production Releases For Which You Would Assume Responsibility: Global Content Analytics v1 and subsequent releases for internal stakeholders, CAM, SIM, and Assemblies base datasets for GAIA use, GAIA base geometry datasets for general internal use in AMPSupport of exploratory use of content analytics by COO-Data Science and Applied AI Engineering, Creation of a product roadmap to guide further releases to follow in FY27
• In Addition, You Will Help Evolve Our Principles And Policies For The Responsible Use Of Customer Content, Including Driving That Evolution Proactively Where Desirable
• To achieve the above, you will partner closely across GAIA and related teams as follows:

Qualifications

• 5+ years as a Product Manager delivering data or analytics products
• Experience defining product vision and strategy
• Experience as an analyst or managing an analytics function
• Proficient in data modeling
• Experience with big data technologies such as Snowflake, Spark, Presto, Hive or similar preferred
• Track record of effective communication on data and analytics topics
• Experience with governance as it applies to data, machine learning, or artificial intelligence