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Matterworks

AI-powered MaaS for metabolomics data

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeSomerville, MA, USA

About the Job

Requirements

  • At least 2 years of professional experience building data pipelines in production.
  • Proficiency in Python and SQL.
  • Working knowledge of cloud data infrastructure; experience with comparable infrastructure stacks is transferable.
  • Demonstrated experience owning a pipeline or dataset end to end, including tests, monitoring, and failures.
  • Comfort working with messy data and formats, including investigating discrepancies between sources.
  • Daily use of AI coding tools, with healthy skepticism about their output on production data correctness.
  • Clear written communication, particularly when explaining failures and changes.
  • Curiosity about science.
  • Interest in contributing to an early-stage startup environment characterized by autonomy, eagerness to learn, and solving novel scientific challenges.

Responsibilities

  • Build, test, instrument, document, and operate well-scoped data pipelines end to end on a schedule.
  • Transform raw data into usable datasets with consistent schemas, trustworthy metadata, and documented definitions.
  • Design, build, and extend data quality checks that compare each build with the previous one before publication and stop the pipeline when checks fail.
  • Ingest public and partner datasets by fetching, converting, validating, and reconciling them against existing data, and improve systems to handle messy scientific and vendor formats at scale.

Desired Qualifications

  • Experience in life sciences, biotechnology, or biochemistry.

About the Company

Matterworks

AI-powered MaaS for metabolomics data

Matterworks uses AI to analyze mass spectrometry data for metabolomics, offering a model-as-a-service platform to researchers in therapeutic research, biomanufacturing, crop science, and animal health. Its Large Spectral Model interprets complex molecular data, and Pyxis provides a turn-key solution that identifyies and quantifies metabolites from raw data in near real-time. This speeds up R&D by turning undecoded signals into actionable biological insights, helping researchers predict outcomes in areas like protein production and sustainable agriculture. The company differentiates itself by delivering end-to-end omics analysis as a service for a broad life sciences audience, focusing on accessibility, speed, and reducing the need for specialized analytics teams to accelerate life sciences R&D.

Company size
11-50
Company stage
Seed
Total funding
$13.8M
Headquarters
Somerville, MA
Founded
2019

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