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Summer Bayesian Jobs (NOW HIRING)

Costello Medical

Statistician Intern

Boston, MA · On-site +1

$26 - $32/hr

We are currently recruiting for start dates in Summer 2026 and you will be asked to state your ... analysis and Bayesian network meta-analysis using both standard and emerging methods. This ...

Costello Medical

Statistician Intern

Boston, MA · On-site

$26 - $32/hr

We are currently recruiting for start dates in Summer 2026 and you will be asked to state your ... analysis and Bayesian network meta-analysis using both standard and emerging methods. This ...

Costello Medical

Statistician Intern

Boston, MA · On-site

$26 - $32/hr

We are currently recruiting for start dates in Summer 2026 and you will be asked to state your ... analysis and Bayesian network meta-analysis using both standard and emerging methods. This ...

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How much do summer bayesian jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for summer bayesian in the United States is $15.89, according to ZipRecruiter salary data. Most workers in this role earn between $13.46 and $17.55 per hour, depending on experience, location, and employer.

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

To thrive as a Bayesian Statistician, you need strong mathematical and statistical knowledge, especially in probability theory, Bayesian inference, and typically a degree in statistics, mathematics, or a related field. Proficiency in statistical programming languages such as R, Python (with libraries like PyMC or Stan), and familiarity with MCMC methods are essential. Critical thinking, problem-solving, and the ability to communicate complex ideas clearly are standout soft skills in this role. These skills ensure accurate data analysis, effective modeling, and clear communication of results for informed decision-making.

What are Summer Bayesians?

A Summer Bayesian is typically a student or researcher who participates in summer programs, workshops, or internships focused on Bayesian statistics and data analysis. These programs often provide intensive training in Bayesian methods, including hands-on projects and collaboration with experts in the field. The goal is to help participants build practical skills in applying Bayesian inference to real-world problems, often in academic or industry settings. Summer Bayesians may come from diverse backgrounds such as statistics, computer science, or engineering.

What is the difference between Summer Bayesian vs Summer Data Analyst?

AspectSummer Bayesian
Required CredentialsTypically requires a background in statistics, mathematics, or data science; familiarity with Bayesian methods and programming languages like R or Python
Work EnvironmentResearch-focused, often in academic or tech companies, involving statistical modeling and data analysis
Employer & Industry UsageUsed in industries like finance, healthcare, and tech for probabilistic modeling and decision-making
Common Search & ComparisonCompared with data analysts for skill overlap and project scope

Summer Bayesian roles focus on advanced statistical modeling using Bayesian methods, requiring strong quantitative skills and programming knowledge. In contrast, Summer Data Analysts typically handle broader data processing and reporting tasks. While both roles involve data work, Summer Bayesian positions emphasize probabilistic modeling and statistical inference, making them more specialized.

What are some common challenges faced by Bayesian statisticians during summer research projects?

Summer research projects for Bayesian statisticians often involve tight timelines and rapidly evolving datasets, which can make it challenging to develop, test, and validate complex models efficiently. Collaborating with interdisciplinary teams—such as domain experts, data engineers, and fellow statisticians—requires clear communication to ensure assumptions and results are well understood by all stakeholders. Additionally, balancing exploratory analysis with rigorous statistical inference is essential to deliver actionable insights within the limited timeframe of a summer program.
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Summer Bayesian jobs near you
Infographic showing various Summer Bayesian job openings in the United States as of May 2026, with employment types broken down into 2% Internship, 37% Full Time, 43% Part Time, 4% Temporary, 12% Contract, and 2% Summer. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $33,041 per year, or $15.9 per hour.
Research Intern - Bayesian Methods in Geometric Computer Vision

Research Intern - Bayesian Methods in Geometric Computer Vision

Microsoft

Redmond, WA • On-site

$8K - $14K/mo

Internship

Posted 16 days ago

Microsoft rating

8.6

Company rating: 8.6 out of 10

Based on 125 frontline employees who took The Breakroom Quiz

47th of 186 rated software companies

Job description

Overview
Research Internships at Microsoft provide a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers, who pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment.
Traditional methods in geometric computer vision, which are still the go-to techniques for robot navigation, three-dimensional (3D) scene reconstruction, and the real-time generation of Augmented Reality/Virtual Reality (AR/VR) assets, are based on frequentist statistical methods, in particular maximum likelihood estimation. The goal of this Research Internship is to develop a basis for the application of Bayesian methods in geometric computer vision, starting with the fundamental problem of 2D and 3D point matching. Candidates should have research-level knowledge of two of the three following topics (and, if required, the drive to learn the third), demonstrated through publications or explicit direction of their PhD work:
Geometric computer vision, including:
  • The pinhole camera model, homographies, essential and fundamental matrix;
  • three-dimensional point triangulation and iterative closest-point methods.
  • Associated statistical methods such as RANSAC and maximum likelihood estimation;
  • estimation of geometric and algebraic errors associated with geometric parameters of interest.

Bayesian statistical theory, including:
  • Jeffreys' and uniform priors;
  • exact and approximate marginalization techniques;
  • nuisance parameters and outliers from a Bayesian perspective.

Rigorous methods in approximation theory, including:
  • Polynomial randomized approximation algorithms;
  • computational complexity classes;
  • approximation methods for discrete problems.

Note that heuristic and learning-based methods are outside the scope of the work. Execution of the Research Internship plan will require efficient implementation of approximation algorithms in the context of one or more problems in geometric computer vision, and the benchmarking of the results against competing methods. Therefore, ability to produce efficient code in Python or C++ is a must.
The Research Internship has the explicit goal of producing a high-quality technical report, which, if the work is successful, will be submitted to an appropriate publication venue.
Responsibilities
Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world's best researchers, Research Interns learn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer.
Qualifications
Required Qualifications
  • Currently enrolled in a PhD program in Mathematics, Statistics, Computer Science or a related STEM field.
  • Completed graduate coursework in at least two of the three topics:
    • Geometric computer vision;
    • Probability and statistics, covering Bayesian theory;
    • Approximation algorithms and computational complexity classes.

Other Requirements
  • Research Interns are expected to be physically located in their manager's Microsoft worksite location for the duration of their internship.
  • In addition to the qualifications below, you'll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter.

Preferred Qualifications
  • Proficiency in the implementation of efficient algorithms, demonstrated by published algorithms or samples of open-source code.
  • Demonstrated ability to understand algorithm benchmarks and evaluation.
  • Experience with writing technical reports and scientific publications.
  • Willingness to learn new topics without being daunted by a steep learning curve.

The base pay range for this internship is USD $6,710 - $13,270 per month. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $8,760 - $14,360 per month.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-intern-pay
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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About Microsoft

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Our infrastructure is comprised of a large global portfolio of more than 100 datacenters and 1 million servers. Our foundation is built upon and managed by a team of subject matter experts working to support services for more than 1 billion customers and 20 million businesses in over 90 countries worldwide. With environmental sustainability and optimization at the forefront of our datacenter design and operations, we continue to grow and evolve as we meet the ever-changing business demands that hold Microsoft as a world-class cloud provider.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Redmond, WA, US

Year founded

1975

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