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CuspAI is a frontier AI company focused on using artificial intelligence to discover breakthrough materials for energy, clean water, computing, and carbon capture. The company's founding team includes world-leading researchers in AI, chemistry, and engineering.
As Head of Data, you will lead the data strategy and team for this rapidly growing organization. You'll define the data foundation of a frontier AI company, working with world-class AI experts and materials science researchers to expand the company's data portfolio and modeling capabilities.
Key responsibilities include:
DATA STRATEGY: Build and own CuspAI's data strategy in partnership with leadership, translating research and commercial priorities into a clear view of needed data assets and acquisition sequencing. Establish an evidence-led framework to identify high-value data opportunities and architect scalable acquisition or generation pathways. Make and defend build-vs-buy-vs-partner decisions with accountability for outcomes.
DATA ACQUISITION & ASSET CREATION: Set up and drive initiatives to acquire and build proprietary data assets through commercial licensing, academic and national lab collaborations, targeted experimental campaigns, high-throughput computational generation, and internal lab data generation. Scope, stand up, and oversee data generation programs end-to-end from experimental design through ML-ready asset delivery. Build and maintain a pipeline of prospective data partners across industry, academia, instrument vendors, simulation vendors, and commercial data providers.
KEY COLLABORATIONS: Own relationships with research leads, codesigning data strategies in their research areas. Identify, evaluate, and propose new data partnerships to the Partnerships team with clear theses on strategic value, data quality, exclusivity, cost, and integration effort. Collaborate with Finance on data budgeting. Design and run the data request process. Act as single point of accountability for data commitments to the research organization.
LEADERSHIP: Lead, grow, and develop the Data team spanning data acquisition, curation, data architecture, and data engineering. Set standards for data quality, provenance, and interoperability. Represent CuspAI's data work to external partners and across the company.
Required qualifications include substantial experience owning data strategy or data acquisition at a research-intensive organization (frontier AI lab, deep-tech, materials/chemicals/energy company, national lab, or research institute) with clear accountability for outcomes. A PhD in Chemistry, Physics, Materials Science, Chemical Engineering, Computational Chemistry, or related discipline (or equivalent scientific research experience) with technical grounding to interrogate data quality and experimental design. Demonstrated experience originating and shaping external data partnerships. Experience managing meaningful budgets with commercial judgment. Experience leading and growing technical teams. Deep familiarity with materials and chemical data landscapes (ICSD, Cambridge Structural Database, NOMAD, Materials Project). Working knowledge of how experimental data is produced (lab workflows, instrument outputs, ELN/LIMS systems, metadata). Technical fluency in Python, SQL, data modeling, and ML training data requirements to work as peer with data engineers and ML researchers.
