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 2026 agentic-AI messaging aligns with buyer budgets shifting from pilots to production.
  • The April 2026 Toshio Mii appointment signals continued Japan expansion and enterprise credibility.
  • Idemitsu's expanded 2023 partnership and Resonac adoption validate repeatable materials-informatics demand.

What critics are saying

  • Enthought depends on a handful of manufacturers like Idemitsu, Resonac, and Tokyo Electron.
  • Agentic AI competitors from Anthropic, OpenAI, and hyperscalers compress Enthought's consulting margin by 2027.
  • If clients internalize Python, MI, and agent workflows, Enthought's services business loses relevance quickly.

What makes Enthought unique

  • Enthought built scientific Python tooling since 2001, shaping modern computational science for R&D teams.
  • Its materials-informatics focus links AI, chemistry, physics, and lab workflows, not generic enterprise software.
  • Japan depth stands out: 2026 chairman Toshio Mii and Tokyo partnerships deepen regional access.

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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

-7%

1 year growth

-7%

2 year growth

-7%
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.

Analytics India Magazine
Jul 21st, 2020
Top Python Libraries For 3D Machine Learning

3D machine learning has gained tremendous popularity in recent years and has become one of the most researched areas in a few years.