
Job Overview
Location
Somerville, MA (Hybrid)
Job Type
Full-time
Category
Data & Analytics
Date Posted
April 9, 2026
Full Job Description
đź“‹ Description
- • As a Data Manager (Bioinformatics / Cheminformatics) at Matterworks, you will build and own the data management practice that transforms complex biological and chemical datasets into high-quality, well-governed training corpora and product-ready data assets, enabling breakthroughs in therapeutic discovery and AI-driven insights.
- • You will partner with scientific, ML, and product teams to define a data roadmap, design repeatable dataset intake workflows, establish curation and governance standards, and build QC/QA frameworks that ensure data consistency, usability, and scalability across omics modalities.
- • Matterworks is an early-stage startup building large-scale deep learning models of biological data to predict phenotypes and behaviors, operating in a flexible hybrid model from Somerville, MA, with a mission to unlock opportunities in therapeutic discovery through AI.
- • You will gain end-to-end ownership of scientific data workflows, develop scalable data governance practices, collaborate cross-functionally with AI, engineering, and product teams, and grow into a leadership role as the data function scales with the company.
Skills & Technologies
About Matterworks, Inc.
Matterworks, Inc. empowers life sciences R&D by transforming biological research from empirical to predictive through its AI-driven platform, Pyxis. Leveraging a Large Spectral Model trained on billions of spectra, Matterworks makes biochemical omics broadly accessible, uncovering hidden predictive power in complex datasets. Their solutions serve biopharmaceutical companies, enabling asset and target discovery, derisking toxicology and safety assessments, predicting clinical outcomes, and optimizing biomanufacturing processes. This innovative approach aims to significantly improve the success rate of life science pipeline R&D by providing deeper biological insights and predictive capabilities, helping to build the future of predictive biology.
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