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Home Based Scientific Software Developer Jobs (NOW HIRING)

Viridien

Scientific Software Developer

Houston, TX · Hybrid

Master's degree or higher in Physics, Engineering, Mathematics, or Computer Science, or 5 years of ... Performance-based monthly bonus averaging at 10-15% at entry level ( contingent on financial ...

Viridien

Scientific Software Developer

Houston, TX · Hybrid

Master's degree or higher in Physics, Engineering, Mathematics, or Computer Science, or 5 years of ... Performance-based monthly bonus averaging at 10-15% at entry level ( contingent on financial ...

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Home Based Scientific Software Developer information

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$83.5K

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How much do home based scientific software developer jobs pay per year?

As of Sep 15, 2026, the average yearly pay for home based scientific software developer in the United States is $102,500.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $115,000.00 per year, depending on experience, location, and employer.

What is a home based scientific software developer?

A Home Based Scientific Software Developer is a professional who designs, develops, and maintains software tools used for scientific research and analysis, while working remotely from home. They often collaborate with scientists, researchers, and engineers to create programs that process data, simulate experiments, or visualize scientific phenomena. This role requires strong programming skills, knowledge of scientific principles, and the ability to work independently using remote communication tools. Home based roles offer flexibility, allowing developers to contribute to research projects and software solutions from anywhere. These professionals are essential in fields like bioinformatics, physics, chemistry, and environmental science.

What are the key skills and qualifications needed to thrive as a home based scientific software developer?

A Home Based Scientific Software Developer needs strong programming skills (often in Python, C++, or MATLAB), a solid background in mathematics or a scientific discipline, and typically at least a bachelor's degree in computer science, engineering, or a related field. Familiarity with scientific computing libraries, version control systems like Git, and experience with cloud-based or distributed computing platforms are commonly required. Excellent problem-solving abilities, self-motivation, and effective remote communication are vital soft skills for success in a home-based setting. These competencies ensure the developer can build reliable, efficient scientific software, collaborate virtually with researchers, and deliver solutions that advance scientific discovery.

What are some common challenges for home based scientific software developers and how can they be addressed?

Home-based scientific software developers often face challenges such as maintaining clear communication with research teams, managing time effectively without in-person supervision, and ensuring access to necessary computing resources. Overcoming these challenges typically involves using collaborative tools like version control systems (e.g., Git), regular video meetings, and cloud-based platforms for code sharing and testing. Establishing a structured daily routine and staying updated with scientific advancements also helps developers stay productive and connected with their team.

What is the difference between Home Based Scientific Software Developer vs Scientific Software Engineer?

AspectHome Based Scientific Software DeveloperScientific Software Engineer
CredentialsBachelor's or Master's in Computer Science, Physics, or related fieldsBachelor's or Master's in Computer Science, Engineering, or related fields
Work EnvironmentRemote, home-based setupTypically office or lab environment, but may include remote work
Industry UsageResearch institutions, academia, biotech, environmental agenciesResearch labs, industry R&D, government agencies
Common Search/ComparisonYesYes

The main difference is that a Home Based Scientific Software Developer primarily works remotely on scientific software projects, often in academia or research settings, while a Scientific Software Engineer may work in more traditional office or lab environments within industry or government. Both roles require similar educational backgrounds and skills, but their work settings and typical employers differ.

What cities are hiring for Home Based Scientific Software Developer jobs?

Cities with the most Home Based Scientific Software Developer job openings:

What are the most commonly searched types of Scientific Software Developer jobs?

The most popular types of Scientific Software Developer jobs are:

What states have the most Home Based Scientific Software Developer jobs?

States with the most job openings for Home Based Scientific Software Developer jobs include:

What are popular job titles related to Home Based Scientific Software Developer jobs?

For Home Based Scientific Software Developer jobs, the most frequently searched job titles are:

Infographic showing various Home Based Scientific Software Developer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 14% Part Time, and 7% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $102,500 per year, or $49.3 per hour.

Scientific Software Developer

Austin, TX • On-site

Enthought
Software Development • 51 - 200 employees
Learn more about Enthoughtexternal

Full-time

Re-posted 16 days ago

Job description

We are hiring a Scientific Software Developer to join our client-facing solution delivery team. Working agent-first, you will pair deep scientific expertise with agentic AI coding tools to move from research question to working software - building data-driven models, AI-based decision-support tools, and analysis pipelines for the world's leading R&D organizations.
Key Responsibilities
  • Design end-to-end scientific solutions - apply deep knowledge of statistics, optimization, machine learning, and related areas to translate client R&D problems into architectures spanning data, models, and user-facing applications.
  • Work agent-first - use AI coding assistants and autonomous coding agents as your default way to explore data, prototype models, build software, write tests, and produce documentation, compressing the path from research question to working solution.
  • Direct AI agents like a technical lead - decompose scientific and engineering problems into well-scoped tasks, give agents the domain context and scientific constraints they need, and iterate 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, and assemble them into web-based solutions involving GUIs, 2D and 3D graphics, and cloud computing.
  • Design AI-enabled and agentic capabilities into client solutions where they add value - held to the same rigor as any other component.
  • Apply judgment about where AI and generative approaches fit and where they don't, balancing speed against reliability and reproducibility.
  • Take part in collaborative development practices - code review, architecture reviews, sprint planning, retrospectives, and daily standups - and 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.

What We Offer
  • Meaningful impact - your work directly advances scientific breakthroughs, from accelerating drug discovery to developing sustainable materials.
  • A front-row seat to agentic AI - work at an automation-first company where every role directs AI tools, and help define how the industry puts them to work.
  • World-class colleagues - collaborate with some of the smartest, kindest scientists and engineers around.
  • Continuous learning - access to Enthought's training programs in Python, machine learning, and scientific computing.
  • A global, collaborative culture across our Austin, Cambridge, and Tokyo offices.
  • Flexible hybrid work based out of our Austin office.
  • Competitive compensation and benefits.

Who Thrives Here
Everyone at Enthought shares a common set of traits: exceptional integrity, analytic intelligence, a sense of urgency, the ability to simplify the complex, openness in communication, empathy for people, and endurance. If you are endlessly curious, take full ownership of your work, and are excited to help shape how science gets done in the era of agentic AI, you will feel at home here.
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