Full-Time

Materials Data Scientist / Scientific Software Developer

Enthought

Enthought

51-200 employees

Science-driven AI solutions for enterprise

No salary listed

Cambridge, UK

Hybrid

Hybrid work based out of the Cambridge office.

Category
Data & Analytics (1)
Required Skills
LLM
Python
Data Science
Machine Learning

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Requirements
  • Deep expertise in materials science and chemistry.
  • Expertise in machine learning and materials informatics.
  • Ability to use AI coding assistants and autonomous coding agents to explore data, prototype models, build software, write tests, and produce documentation.
  • Ability to provide domain context and physical constraints for AI agents and evaluate results for correctness and defensibility.
  • Ability to solve complex research and product-development problems with client researchers and business leaders.
  • Ability to design AI-enabled and agentic capabilities, including retrieval over materials data, with appropriate rigor.
  • Ability to judge when artificial intelligence and generative approaches are appropriate for small, sparse, and noisy materials research and development datasets.
  • Ability to handle client data and intellectual property responsibly using approved, secure artificial-intelligence tool configurations.
  • Ability to participate in code reviews, architecture reviews, sprint planning, retrospectives, and daily standups.
  • Ability to interface directly with clients to define, demonstrate, and refine solutions.
Responsibilities
  • Design end-to-end materials informatics solutions by translating client research and development problems into architectures spanning data, models, and user-facing applications.
  • Use AI coding assistants and autonomous coding agents to explore data, prototype models, build software, write tests, and produce documentation.
  • Direct artificial-intelligence agents as a technical lead by decomposing materials and chemistry problems into well-scoped tasks and iterating toward correct, defensible results.
  • Solve complex research and product-development problems in close collaboration with client researchers and business leaders.
  • Build data-driven models, AI-based decision-support tools, and automated analysis pipelines.
  • Assemble models, tools, and pipelines into web-based solutions involving graphical user interfaces, two-dimensional and three-dimensional graphics, and cloud computing.
  • Design AI-enabled and agentic capabilities into client solutions where they add value, including retrieval over materials data.
  • Participate in collaborative development practices, including code review, architecture review, sprint planning, retrospectives, and daily standups.
  • Interface directly with clients to define, demonstrate, and refine solutions.
  • Handle client data and intellectual property responsibly using AI tools only in approved, secure configurations.

Enthought helps businesses turn science into AI and data solutions by pairing scientists and software developers to guide projects from strategy to deployment. They build vertically integrated AI applications with an accessible Python interface for continuous optimization that works with any data state. They differentiate themselves by combining domain science with software development to deliver end-to-end, domain-specific AI tailored to a company’s data and value, not generic tools. Their goal is to accelerate digital transformation by extracting concrete business value from data and empowering teams to design and deploy AI.

Company Size

51-200

Company Stage

N/A

Total Funding

$3.6M

Headquarters

Austin, Texas

Founded

2001

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Simplify Jobs

Simplify's Take

What believers are saying

  • Enthought's site updated July 27, 2026, and careers page shows active hiring.
  • The August 2026 job ad seeks an agent-first materials scientist, signaling product demand.
  • Idemitsu and Resonac expansions validate Enthought's materials informatics wedge in Japan.

What critics are saying

  • Enthought still sells services-heavy AI consulting; revenue scales poorly without repeatable software.
  • Tokyo Electron's five-year commitment anchors concentration risk if one Japanese account churns.
  • A failed Japan expansion would leave Enthought dependent on low-margin custom projects.

What makes Enthought unique

  • Enthought's 2026 pitch centers on agentic AI for scientific R&D, not generic enterprise software.
  • Its materials informatics stack combines informed machine learning, uncertainty quantification, and active learning.
  • Enthought Japan deepens embedded delivery, led by Toshio Mii on April 16, 2026.

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Benefits

Performance based bonuses

Medical, dental, vision, and life insurance

401(k)

Stock options

Work-life balance

Hybrid work – remote 60% / in-office 40%

Company sponsored lunches and happy hours

Free parking

Growth & Insights and Company News

Headcount

6 month growth

-10%

1 year growth

-10%

2 year growth

-10%
Business Wire
Nov 13th, 2024
Idemitsu Expands Partnership With Enthought to Accelerate Product Innovation Using Materials Informatics

As it runs the last leg of the race to mass-production and commercialization, Idemitsu invested in digitalization and partnered with Enthought in 2023 to accelerate their materials and process development efforts and to provide the insights needed to scale up rapidly.

Enthought
Sep 1st, 2021
Enthought, Inc. launches Enthought Edge

Austin, TX – September 1, 2021 – Enthought, the leading provider of services and technology powering digital transformation for science, today announced the launch of Enthought Edge, a DataOps solution built specifically to support the unique needs of R&D data.

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Jul 21st, 2020
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