Head of Data Partnerships

About 83 Sciences

AI-native materials discovery powered by unpublished experimental data

Tech

Our platform, Dalton, turns messy, heterogeneous lab data into structured, queryable knowledge. The technical problems we're working on include: Multimodal data capture: OCR pipelines that convert handwritten lab notebook pages into structured entries and speech-to-text tools Scientific data analysis: automated PXRD/characterization analysis: phase prediction, peak identification, anomaly detection Chemistry-specific ML: models tuned on a lab's full experimental history (including failed runs) to predict synthesizability and reaction outcomes and suggest optimal process conditions You'll work across the full stack (data pipelines, ML, and product) with real lab data and direct feedback from working scientists.

The role

## Head of Data Partnerships83 Sciences is building the data and AI infrastructure for scientific discovery. Almost 90% of experimental data is discarded, losing over $100B in R&D value every year. 83 Sciences turns unused experimental data into the materials and manufacturing processes powering the next industrial revolution.Our ambition is to **own or license the world’s experimental data** and use it to build better models for science.## The RoleYour first job is to build our university data network, starting with individual labs and scaling to departments and institution-wide partnerships. From there, you’ll expand into industry R&D and other major sources of proprietary experimental data.You will:* Build and close partnerships with universities and research labs* Navigate complex relationships across faculty, research leadership, tech transfer, legal, and administrators* Structure data access, licensing, and partnership agreements* Translate partner needs into product requirements* Work closely with product and engineering to build tools researchers actually want to use* Create scalable partnership models that can grow from one lab to an entire institution* Expand the network over time into industry R&D and other proprietary data sourcesWe’re looking for someone who can operate like a founder: build relationships from scratch, manage ambiguity, move quickly, and turn partner insight directly into product and strategy.**Your mandate: build the network that gives 83 Sciences access to the world’s most valuable experimental data.**