TetraScience

Scientific Data Engineer

United States

Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Scientific Data, AI Cloud, Biotechnology, PharmaceuticalsIndustries

Job Description: Data Scientist, Scientific AI

Position Overview

TetraScience is seeking a talented Data Scientist to join our team and contribute to the Scientific AI revolution. We are the category leader in scientific data and AI cloud solutions, enabling next-generation lab data management and AI-enabled outcomes. This role involves researching data acquisition strategies, developing file parsers, designing data models and pipelines, and building visualizations to drive customer value.

About TetraScience

TetraScience is the Scientific Data and AI Cloud company. We are catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which we bring to life in a growing suite of next gen lab data management solutions, scientific use cases, and AI-enabled outcomes. TetraScience is the category leader in this vital new market, generating more revenue than all other companies in the aggregate. In the last year alone, the world’s dominant players in compute, cloud, data, and AI infrastructure have converged on TetraScience as the de facto standard, entering into co-innovation and go-to-market partnerships.

We encourage candidates to carefully review the "Tetra Way" letter authored by our CEO, Patrick Grady, to understand our values and ethos.

Responsibilities

  • Research data acquisition strategy for scientific lab instrumentation.
  • Research and productionize file parsers for instrument output files (e.g., .xlsx, .pdf, .txt, .raw, .fid, various vendor binaries).
  • Design and build data models and corresponding data pipelines.
  • Develop unit tests, integration tests, and reusable utility functions.
  • Cross-analyze instrument data to design common data model components.
  • Build visualizations, reports, and dashboards using tools like Streamlit, Tableau, and Jupyter Notebook.
  • Drive customer value by testing and ensuring solutions meet requirements.

Requirements

  • Must-have:
    • 3+ years of experience in Python and SQL.
    • PhD degree in biology, chemistry, or a relevant field.
    • Extensive wet lab experience, preferably with HPLC and Mass Spec.
    • Experience working with one or more of the following instruments:
      • Waters LCs with Empower software and MassLynx software.
      • Thermo Fisher LCs with Chromeleon software and Xcalibur software.
      • Cytiva LCs with Unicorn software.
      • Shimadzu LCs with LabSolution software.
      • Sciex LCs with Sciex software.
      • Agilent LCs with OpenLab software and ChemStation software.
  • Plus:
    • Experience with data plotting and dashboarding tools like Streamlit, Tableau, Jupyter Notebook.
  • Skills & Attributes:
    • Passionate about data problems and using AI/LLM for creative solutions.
    • Excellent communication skills and attention to detail.
    • Confidence to take ownership of project delivery.
    • Ability to quickly understand highly technical products and communicate effectively with product management and engineering.
    • Proactive problem-solving skills.
    • High-bandwidth: thrives when managing multiple simultaneous projects.
    • Intellectually curious with a drive to learn.
    • Ability to think creatively about solving project risks without compromising quality.
    • Team player with a willingness to "roll up your sleeves."

Benefits

  • 100% employer-paid benefits for eligible employees and their immediate family members.
  • Unlimited Paid Time Off (PTO).
  • 401K.
  • Flexible working arrangements (Remote work).
  • Company-paid Life Insurance, LTD/STD.
  • Culture of continuous improvement with career growth and coaching opportunities.

Additional Details

  • Employment Type: Full-time
  • Location Type: Remote
  • Language: English
  • Department: Engineering
  • Published: 2025-07-09
  • Visa Sponsorship: Not currently provided.

Skills

Data Engineering
Data Modeling
Data Pipelines
File Parsers
Streamlit
Tableau
Jupyter Notebook
Scientific Data
AI

TetraScience

Cloud platform for scientific data management

About TetraScience

TetraScience offers a cloud-based platform called the Scientific Data Cloud, which helps biopharmaceutical companies manage and harmonize their scientific data for research and development, quality assurance, and manufacturing. The platform connects various lab instruments and software, streamlining data management and significantly reducing task completion time. TetraScience's vendor-neutral and open design allows it to work with any lab equipment, making it a flexible solution in the life sciences sector. The company's goal is to enhance scientific outcomes by preparing data for artificial intelligence and machine learning applications.

Boston, MassachusettsHeadquarters
2019Year Founded
$113.8MTotal Funding
SERIES_BCompany Stage
AI & Machine Learning, Biotechnology, HealthcareIndustries
51-200Employees

Benefits

Unlimited PTO
100% company paid health, dental, & vision
Company paid life insurance
401k savings
Company paid disability insurance
Equity program
Flexible work arrangements

Risks

Rapid AI development may outpace TetraScience's integration capabilities, risking obsolescence.
Dependency on partners like Google Cloud and NVIDIA could pose risks if disrupted.
International expansion may expose TetraScience to regulatory and compliance challenges.

Differentiation

TetraScience offers a vendor-neutral, open, cloud-native platform for scientific data management.
The platform integrates with any lab equipment or software, enhancing flexibility and adaptability.
TetraScience's Scientific Data Cloud centralizes and harmonizes data, preparing it for AI/ML applications.

Upsides

Partnerships with NVIDIA and Google Cloud enhance AI-native scientific datasets and capabilities.
Collaboration with Databricks accelerates the Scientific AI revolution in life sciences.
Bayer AG partnership maximizes scientific data value, driving innovation in biopharma.

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