Head of Data

About the role

CuspAI is seeking a Head of Data to define and expand the company's data foundation. This role involves leading the data strategy and team for a frontier AI company focused on materials science. You will work with leading experts to grow our data portfolio and enhance modeling capabilities.

Key facts

What you'll do

• Develop and own CuspAI's data strategy, aligning with research and commercial goals.
• Create frameworks for identifying valuable data opportunities and designing acquisition or generation methods.
• Make and justify decisions on building, buying, or partnering for data, taking responsibility for outcomes.
• Lead initiatives to acquire and build proprietary data assets through various collaborations and campaigns.
• Manage data generation programs from initial design to delivery of ML-ready assets.
• Build relationships with research leads and identify new data partnerships.
• Collaborate with the Finance team on data budget allocation.
• Design and manage the data request process.
• Lead and grow the Data team, covering acquisition, curation, architecture, and engineering.
• Establish and uphold data quality, provenance, and interoperability standards.
• Represent CuspAI's data work to external partners and across the company.

Requirements

• Significant experience managing data strategy or acquisition in a research-focused setting (AI lab, deep-tech, materials/chemicals/energy company, national lab, research institute), with accountability for results.
• PhD in Chemistry, Physics, Materials Science, Chemical Engineering, Computational Chemistry, or similar scientific research experience, with technical depth to evaluate data quality and experimental design.
• Proven experience initiating and shaping external data partnerships, including sourcing, diligence, and working with commercial and legal teams.
• Experience managing a substantial budget, with commercial judgment for prioritizing spend and negotiating investments.
• Experience leading and developing technical teams, with a desire to build a team.
• Deep understanding of materials and chemical data landscapes (e.g., ICSD, Cambridge Structural Database, NOMAD, Materials Project) and their practical applications.
• Practical knowledge of experimental data production: lab workflows, instrument outputs, ELN/LIMS systems, unit conventions, metadata challenges, and preparing data for ML.
• Technical fluency in Python, SQL, data modeling, and ML training data requirements to collaborate with engineers and researchers and evaluate proposals.
• Exceptional communication and relationship-building skills.

Nice to have

• Direct experience with high-throughput experimentation, lab automation, robotics, or self-driving lab platforms.
• Hands-on familiarity with characterization techniques (XRD, spectroscopy, adsorption isotherms, electron microscopy) and their data limitations.
• Experience with high-throughput computational screening and DFT codes (e.g., VASP, Quantum ESPRESSO) and the economics of large-scale computational data generation.
• Experience negotiating data-sharing agreements, data standards, and navigating IP, licensing, and confidentiality for scientific data.
• A strong existing network in materials research, national labs, instrument vendors, or industrial R&D.
• Familiarity with data engineering practices (ETL/ELT, schema validation, data contracts, workflow orchestration) to ensure high standards.

Skills & tools

• Python
• SQL
• Data modeling
• ML training data requirements
• ICSD
• Cambridge Structural Database
• NOMAD
• Materials Project
• ELN/LIMS systems
• VASP
• Quantum ESPRESSO

Practical notes

Travel may be required for collaboration. Benefits include 21 days holiday (SG), parental leave (26 weeks primary, 12 weeks secondary caregiver), and a professional development budget. CuspAI is an equal opportunities employer and encourages applications from diverse backgrounds. Accommodations for the interview process are available upon request.