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Scientific Programmer Jobs in Massachusetts (NOW HIRING)

BioTalent

Founding Scientific Lead

Boston, MA · On-site

You will partner closely with engineering, AI, and product teams to define scientific standards, validate outputs, and help build intelligent systems capable of supporting research and laboratory ...

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Scientific Programmer information

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$12

$43

$78

How much do scientific programmer jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for scientific programmer in Massachusetts is $43.54, according to ZipRecruiter salary data. Most workers in this role earn between $16.78 and $62.74 per hour, depending on experience, location, and employer.

What is a scientific programmer?

Scientific programmers are professionals who develop, implement, and optimize software solutions for scientific research and data analysis. They work closely with scientists and researchers to translate complex scientific problems into computational algorithms, scripts, and tools. Their work often involves programming in languages like Python, C++, or R, and may include tasks such as data processing, simulation, modeling, and visualization. Scientific programmers play a crucial role in advancing research by making scientific computations more efficient and reproducible.

What does a scientific programmer do?

The duties of a scientific programmer are to design a variety of tools for researchers to perform statistical and mathematical modeling on large datasets. They often work within a specific framework or software, and their responsibilities are to script tools that make it easier for scientists to use the programs or models. Their duties may include designing a new user interface or creating shell scripts for the UNIX or Linux operating systems. A scientific programmer also conducts code review and quality assurance tasks to ensure that programs are ready to be used. Qualifications include a bachelor’s degree in computer science, bioinformatics, or computational biology. If you want to specialize in a particular discipline, you may need additional experience or advanced qualifications.

What are the key skills and qualifications needed to thrive as a scientific programmer, and why are they important?

To thrive as a Scientific Programmer, you need a solid background in computer science, mathematics, or a related field, along with strong programming skills in languages like Python, C++, or R. Familiarity with scientific computing libraries (such as NumPy, SciPy), data analysis tools, and version control systems like Git is typically required, and experience with high-performance computing or parallel processing is a plus. Strong problem-solving abilities, attention to detail, and effective communication are key soft skills that distinguish top performers in this role. These skills and qualities are crucial for developing reliable, efficient code to support complex scientific research and for collaborating effectively within multidisciplinary teams.

How does a scientific programmer typically collaborate with researchers and other technical staff on projects?

Scientific Programmers often work closely with research scientists, data analysts, and IT teams to develop and optimize software tools for scientific studies. They participate in project meetings to understand research goals, translate scientific requirements into code, and troubleshoot issues that arise in computational workflows. Effective communication and teamwork are essential, as Scientific Programmers must ensure their solutions align with both technical standards and the scientific objectives of the research team.

What is the difference between Scientific Programmer vs Data Analyst?

AspectScientific ProgrammerData Analyst
Required CredentialsBachelor's or higher in Computer Science, Physics, or related fields; programming skillsBachelor's or higher in Statistics, Data Science, or related fields; analytical skills
Work EnvironmentResearch labs, scientific institutions, academia, industry R&DBusiness, finance, healthcare, marketing sectors
Employer & Industry UsageResearch organizations, universities, scientific companiesCorporations, consulting firms, government agencies
Common Search & Comparison IntentUnderstanding technical roles in scientific computingAnalyzing data to inform decisions

Scientific Programmers focus on developing software and algorithms for scientific research, often working with complex simulations and data modeling. Data Analysts interpret data sets to generate insights and support decision-making. While both roles require strong programming skills and analytical thinking, Scientific Programmers are more involved in software development for scientific purposes, whereas Data Analysts focus on data interpretation and reporting.

Is programming a well paid job?

Programming jobs, including roles like scientific programmers, tend to offer competitive salaries that vary based on experience, education, and location. Skilled programmers with expertise in specific tools or languages often earn higher wages, especially in industries like technology, finance, and research. Overall, programming can be a well-paid career compared to many other fields.
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Scientific Programmer jobs near you
Infographic showing various Scientific Programmer job openings in Massachusetts as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 82% Full Time, 14% Part Time, and 2% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution, with an average salary of $90,557 per year, or $43.5 per hour.

Founding Scientific Lead

BioTalent

Boston, MA • On-site

Other

Medical, Dental, Vision, PTO

Posted 15 days ago

Job description

Founding Scientific Lead

Location: US-based | Onsite, hybrid, or flexible working arrangements available

Founding team opportunity | Potential Chief Scientific Officer progression

The Role

We are seeking an experienced scientific leader to serve as the company's first senior scientist, helping bridge cutting-edge biology, AI, and automation. This individual will lead the development of computational biology workflows, ensure scientific rigor across products and outputs, and act as the key scientific authority within the business.

You will partner closely with engineering, AI, and product teams to define scientific standards, validate outputs, and help build intelligent systems capable of supporting research and laboratory workflows. As the organization grows, there is a clear pathway to evolve into a Chief Scientific Officer role.

What You'll Accomplish

  • Lead computational biology workflows: Design, build, and optimize end-to-end computational and experimental workflows that transform scientific questions into actionable results.
  • Drive laboratory automation: Translate manual laboratory processes into scalable and automated workflows, ensuring scientific requirements are accurately reflected in automation systems.
  • Support AI-driven scientific initiatives: Contribute to the evaluation, refinement, and implementation of AI-enabled scientific tools and research workflows.
  • Act as the scientific authority: Review protocols, workflows, and outputs across a broad range of scientific disciplines, ensuring scientific accuracy and quality.
  • Maintain scientific integrity: Oversee scientific accuracy in customer-facing, investor-facing, and internal materials.
  • Develop validation frameworks: Create evaluation criteria, datasets, quality controls, and scientific review processes to support product development.
  • Build and grow scientific teams: Identify capability gaps and recruit scientists and subject matter experts as the organization expands.
  • Engage with customers and stakeholders: Serve as a scientific representative to clients, partners, and the wider research community.
  • Monitor industry developments: Track emerging technologies, methodologies, and trends across life sciences, drug discovery, and research services.
  • Help shape the future of AI-enabled research: Contribute to the development of scalable, data-driven approaches to scientific experimentation and decision-making.

Who You Are

  • Highly proactive and comfortable operating in fast-moving, ambiguous environments.
  • Practical and execution-focused, with a strong preference for testing ideas through data and experimentation.
  • Able to balance scientific rigor with business and product needs.
  • Strong communicator capable of translating complex scientific concepts into actionable guidance for technical and non-technical stakeholders.
  • Comfortable collaborating across science, engineering, AI, and product teams.
  • Demonstrates intellectual honesty and a commitment to evidence-based decision-making.
  • Possesses broad scientific exposure across multiple stages of research and development.

Technical & Scientific Experience

  • PhD in Life Sciences, Computational Biology, Bioinformatics, Biotechnology, or a related discipline (or equivalent industry experience).
  • Extensive hands-on laboratory and scientific research experience across multiple experimental techniques and modalities.
  • Proven experience designing and managing computational biology workflows and data-driven research programs.
  • Strong understanding of scientific reproducibility, validation, experimental design, and quality control.
  • Ability to work effectively alongside software engineers, data scientists, and AI researchers.
  • Experience collaborating with external research organizations, CROs, laboratories, or scientific service providers.
  • Strong publication record or demonstrated scientific impact within academia or industry.
  • Proficiency with scientific programming and data analysis tools such as Python and/or R.
  • Experience leveraging AI, machine learning, or data science tools within research environments is highly desirable.
  • Interest in the opportunities and limitations of AI-enabled scientific discovery and automation.

Compensation & Benefits

  • Competitive base salary.
  • Meaningful equity package aligned with experience and impact.
  • Medical, dental, and vision coverage.
  • Paid time off and company holidays.
  • Opportunity to influence company strategy, scientific direction, and long-term growth from an early stage.


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