Data Partnerships Lead

Tencent•Palo Alto, CA

22h•Onsite

About The Position

We are seeking a Data Partnership Lead to drive data operations and strategies for our frontier AI research initiatives. In this role, you will design end-to-end data acquisition strategies, manage key vendor relationships, and own the data pipeline from requirements to production. This role requires a unique blend of technical depth—to evaluate what constitutes high-quality training data—and operational excellence to execute at a global scale.

Requirements

Demonstrated expertise in high-leverage technical environments, with a strong background in Technical Program Management (TPM), AI Data Operations, Strategic Tech Deals, Data Licensing, or Management Consulting.
Optimize Data Ingestion Workflows: Standardize external dataset specifications and integrate them into internal data processing and pre-training workflows to realize scalable asset accumulation.
Deep operational knowledge of North American data commercial compliance rules and IP licensing architectures.

Responsibilities

Execute End-to-End Data Strategy: Partner directly with foundational model research and algorithm leaders to identify technical data gaps, translating research roadmaps into targeted global sourcing and supplementation strategies.
Drive Strategic Partnerships: Own the full lifecycle of high-value technical data acquisition across North American commercial vendors, research networks, and open-source communities—from initial sourcing and executive pitching to structured commercial negotiation.
Establish Quality & Evaluation Metrics: Collaborate with engineering teams to build data evaluation standards, assessing the technical quality, scarcity, and training utility of external assets to ensure they meet strict algorithmic benchmarks.
Navigate Complex Data Governance: Work cross-functionally with Legal, Privacy, and Security teams to structure licensing, provenance, and anonymization terms (including CCPA/CPRA and broader data regulations) that guarantee legal training and commercial usability
Scale Data Operations: Build robust, long-term vendor and partner ecosystems, managing delivery SLAs and pipeline tracking to accelerate research velocity without sacrificing quality.