As a Tech Strategy Product Manager, you will conduct rigorous, deep-dive investigations into Google's hardest long-range strategic questions, providing data-driven clarity needed for executive decision-making. You will model complex scenarios and trade-offs to surface opinionated strategies for maximizing AI value across Google.

Key responsibilities include:

• Investigative Modeling: Conducting deep-dive investigations into Google's hardest long-range strategic questions, providing data-driven clarity needed for executive decision-making.
• Scenario Architecture: Modelling complex scenarios and trade-offs to surface opinionated strategies for maximizing AI value across Google.
• SVP+ Content Support: Contributing to the development of high-stakes presentations, communications, and mandates for SVP-level forums, ensuring technical accuracy and narrative flow.
• Cross-Functional Partnership: Acting as a bridge between technical teams and strategy, partnering with virtual teams across Google to ensure product and policy plans are grounded in reality.
• Execution & Monitoring: Helping maintain per-mandate monitoring views to keep programs accountable; collaborating with MLSA to ensure company-wide mandates are organized and delivering on goals.
• Strategic Cataloging: Maintaining a 'living catalog' of ongoing experiments and proposed innovations across Google to identify topics worthy of senior executive discussion.

This role is for you if you demonstrate the analytical rigor and strategic curiosity required to sustain a high level of performance across complex, pan-Google workstreams,pairing a 'big picture' perspective with the ability to remain precise and detail-oriented at the speed of an SVP-led forum.

You should have a BA/BS degree or equivalent practical experience in a technical and/or business area, with 5+ years of experience in product management, management consulting, or a high-growth corporate strategy role. Exceptional organisational talent and experience running high-velocity, high-impact programs are also essential.

In addition, familiarity with the role of compute and data in building LLMs and the technical capabilities of these models would be an advantage.

XML job scraping automation by YubHub