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Computational Statistics Jobs (NOW HIRING)

Alljoined

Computational Neuroscientist

San Francisco, CA · On-site

$120K - $160K/yr

Extensive experience using advanced computational, statistical, and modeling skills to analyze and interpret neuroimaging data. * A strong grasp of psychophysics and human behavior. * Demonstrated ...

Kizuki International LLC

Research Analyst

Redmond, WA · On-site

$72K/yr

Candidate must have at least a Master's degree in Applied Mathematics, Statistics, Financial Engineering, Quantitative Finance, or Computational Finance and Risk Management. Candidate duties will ...

Neptune Bio

Computational Biologist

New York, NY · On-site

Solid understanding of statistics, data modeling, and modern machine learning approaches. * Experience deploying and scaling computational pipelines on cloud platforms (AWS, GCP, or similar)

Neptune Bio

Computational Biologist

New York, NY

Solid understanding of statistics, data modeling, and modern machine learning approaches. * Experience deploying and scaling computational pipelines on cloud platforms (AWS, GCP, or similar)

Verge Genomics

Computational Biologist

San Francisco, CA · On-site +1

PhD in computational biology, AI/ML, applied statistics, biophysics, or , * MS and professional experience in relevant fields. * ≥5 years of experience working in applied computational biology and ...

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How much do computational statistics jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for computational statistics in the United States is $54.93, according to ZipRecruiter salary data. Most workers in this role earn between $46.88 and $73.56 per hour, depending on experience, location, and employer.

Is statistician a high paying job?

A statistician is generally considered a well-paying profession, with median salaries often exceeding national averages for many other roles. Salaries can vary based on experience, education, industry, and location, with those working in data-intensive fields or in senior positions earning higher compensation. Strong skills in statistical software and data analysis can also influence earning potential.

What is the difference between Computational Statistics vs Data Scientist?

AspectComputational StatisticsData Scientist
Required CredentialsDegree in Statistics, Mathematics, or related fieldDegree in Computer Science, Statistics, or related field
Work EnvironmentResearch labs, academia, data analysis teamsTech companies, consulting firms, diverse industries
Employer & Industry UsageAcademic institutions, research organizations, analytics teamsBusiness, technology, finance, healthcare
Common Search & Comparison IntentUnderstanding specialized statistical modeling and algorithmsBroader data analysis, machine learning, and business insights

Computational Statistics focuses on developing and applying statistical algorithms and models using computational methods, often emphasizing theoretical foundations. Data Scientists utilize these techniques along with programming and data manipulation skills to extract insights from large datasets across various industries. While there is overlap, Computational Statistics is more research-oriented, whereas Data Science covers a broader range of data analysis tasks.

What are the common challenges faced by professionals in computational statistics, and how can they be addressed?

Professionals in computational statistics often encounter challenges such as managing large, complex datasets, ensuring computational efficiency, and translating statistical findings into actionable insights for non-technical stakeholders. Addressing these challenges typically involves staying updated with the latest software tools, collaborating closely with data engineers and domain experts, and continuously improving communication skills to explain technical results clearly. Proactively seeking opportunities for cross-functional teamwork and ongoing professional development can also help computational statisticians navigate these complexities and advance in their careers.

Is AI replacing statisticians?

Computational statisticians use statistical methods and programming skills to analyze data and develop models. AI tools can automate certain tasks, but statisticians are essential for designing experiments, interpreting results, and ensuring data quality. Their expertise remains valuable in developing, validating, and applying AI and machine learning models effectively.

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

To thrive as a Computational Statistician, you need a solid background in statistics, mathematics, and computer science, usually supported by at least a master's degree in a related field. Expertise in programming languages such as R or Python, experience with statistical software, and familiarity with data management tools are typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret data and present findings clearly. These skills are crucial for designing robust statistical models, extracting actionable insights from complex datasets, and supporting data-driven decision-making.

What is computational statistics?

Computational statistics is a field within data analysis that involves developing and applying algorithms and computer-based methods to analyze large and complex datasets. It combines statistical theory with programming skills, often using tools like R or Python, to perform simulations, model fitting, and data visualization efficiently.

Does the FBI hire mathematicians?

Yes, the FBI hires mathematicians, often under roles such as cryptanalysts, data analysts, or intelligence analysts. These positions typically require strong skills in statistics, coding, and problem-solving, and may require security clearances and relevant educational backgrounds such as mathematics or computer science.
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Computational Statistics jobs near you
Infographic showing various Computational Statistics job openings in the United States as of July 2026, with employment types broken down into 3% Internship, 88% Full Time, and 9% Contract. Highlights an 91% In-person, and 9% Remote job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

Computational Neuroscientist

Alljoined

San Francisco, CA • On-site

$120K - $160K/yr

Full-time

Medical, Retirement

Re-posted 5 days ago

Job description

About Alljoined
Alljoined is creating a future where humans are fully understood and augmented by technology. Our work solves the communication bottleneck between humans and computers by decoding thoughts from the brain, entirely non-invasively. We apply deep learning research to large scale EEG datasets to decode multimedia input, eventually moving to internal thought. We are state-of-the art in capabilities and are fully vertically integrated. Our goal is to develop a general consumer interface to completely transform how we can live our lives.
We are actively growing our world-class team of researchers to build the next interface to improve individual lives as well as the well-being of society as a whole.
About the Role
As a Computational Neuroscientist, you will play a pivotal role in advancing our research. Using computational and neuroimaging techniques, you will design and iterate on stimulus paradigms at scale in collaboration with our research team, and perform comprehensive analyses on collected date to uncover insights into various paradigms and architectures. You will work with a team of hands-on research coordinators who will handle much of the collection work to get data at scale, and collaborate with other engineers and researchers, to design experiments to optimize next-generation neural decoding approaches.
About You
  • PhD/postdoc in neuroscience or a related field.
  • Extensive experience in designing and executing neuroscience studies, including the analysis of functional brain imaging data (EEG, fMRI).
  • Proficiency in Python (MNE, Numpy, PyschoPy) and associated machine learning frameworks (PyTorch, Sci-Py, Scikit-Learn).
  • Extensive experience using advanced computational, statistical, and modeling skills to analyze and interpret neuroimaging data.
  • A strong grasp of psychophysics and human behavior.
  • Demonstrated ability to conduct independent research and collaborate in an interdisciplinary setting.

Compensation Range
$140,000 - $180,000+ /year
While this represents our expected range based on market data, final compensation will be determined based on your specific skills and experience and may be outside this range.
Benefits
  • Competitive equity compensation at a seed stage startup
  • Options for housing support
  • Visa sponsorship
  • 3% 401k matching
  • Health insurance

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