1

Internship Bayesian Jobs (NOW HIRING)

Laboratory or human subjects research experience (academic lab, thesis project, internship, or publication). * Experience with research statistics (e.g., parametric, nonparametric, or Bayesian ...

... complex Bayesian network meta-analysis using both standard and emerging methods. The Senior ... There may also be opportunities to line manage and mentor our Statistician Interns. Career ...

... complex Bayesian network meta-analysis using both standard and emerging methods. The Senior ... There may also be opportunities to line manage and mentor our Statistician Interns. Career ...

... complex Bayesian network meta-analysis using both standard and emerging methods. The Senior ... There may also be opportunities to line manage and mentor our Statistician Interns. Career ...

... complex Bayesian network meta-analysis using both standard and emerging methods. The Senior ... There may also be opportunities to line manage and mentor our Statistician Interns. Career ...

Laboratory or human subjects research experience (academic lab, thesis project, internship, or publication). * Experience with research statistics (e.g., parametric, nonparametric, or Bayesian ...

... complex Bayesian network meta-analysis using both standard and emerging methods. The Senior ... There may also be opportunities to line manage and mentor our Statistician Interns. Career ...

next page

Showing results 1-20

Internship Bayesian information

See salary details

$9

$17

$23

How much do internship bayesian jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for internship bayesian in the United States is $17.31, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What is an Internship in Bayesian analysis?

An Internship in Bayesian analysis is a temporary, practical position focused on applying Bayesian statistical methods to real-world problems. Interns typically work under the supervision of experienced data scientists or statisticians, assisting with research, data modeling, and computational analysis using Bayesian techniques. These internships are valuable for students or recent graduates looking to gain hands-on experience in probabilistic modeling, data analysis, and statistical inference. Such internships often require a strong mathematical background and familiarity with programming languages like Python or R.

What are some common challenges interns face when working on Bayesian analysis projects, and how can they overcome them?

Interns working on Bayesian analysis projects often encounter challenges such as understanding complex statistical principles, learning new software (like Stan or PyMC), and interpreting probabilistic results. To overcome these obstacles, it's helpful to actively seek guidance from mentors, participate in team discussions, and utilize available learning resources. Collaborating closely with experienced team members and regularly reviewing project code and results can accelerate learning and help interns gain confidence in applying Bayesian methods to real-world problems.

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

To thrive in a Bayesian Internship, you need a solid background in statistics, probability theory, and data analysis, typically supported by coursework or a degree in mathematics, statistics, or a related field. Familiarity with programming languages such as Python or R, and experience with statistical software and Bayesian modeling tools (e.g., Stan, PyMC) are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help interns interpret results and collaborate with research teams. These skills are essential for accurately applying Bayesian methods to real-world data and effectively communicating insights.

What is the difference between Internship Bayesian vs Data Analyst Intern?

AspectInternship BayesianData Analyst Intern
Required CredentialsRelevant coursework in Bayesian statistics, basic programming skillsStatistics, data analysis, programming knowledge
Work EnvironmentResearch-focused, collaborative teams in tech or research firmsBusiness or tech companies, data-driven projects
Employer & Industry UsageUsed in research, AI, machine learning sectorsCommon in finance, marketing, tech industries
Search & Comparison IntentUnderstanding roles involving Bayesian methodsExploring data analysis internship opportunities

Internship Bayesian typically involves applying Bayesian statistical methods in research or AI projects, requiring knowledge of Bayesian theory and programming. Data Analyst Internships focus on analyzing datasets, creating reports, and supporting business decisions. While both roles involve data skills, Internship Bayesian emphasizes probabilistic modeling, whereas Data Analyst Internships focus on data visualization and reporting.

More about Internship Bayesian jobs
What cities are hiring for Internship Bayesian jobs? Cities with the most Internship Bayesian job openings:
What are the most commonly searched types of Bayesian jobs? The most popular types of Bayesian jobs are:
What states have the most Internship Bayesian jobs? States with the most job openings for Internship Bayesian jobs include:
Infographic showing various Internship Bayesian job openings in the United States as of July 2026, with employment types broken down into 43% As Needed, 24% Full Time, 6% Part Time, 25% Temporary, 1% Nights, and 1% Summer. Highlights an 67% Physical, 2% Hybrid, and 31% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.
Research Data Analyst

Research Data Analyst

Senseye

Austin, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago


Job description

About Us
Senseye is a NeuroTechnology Company in Austin, TX on the cusp of revolutionizing Mental Health. Over the past 6 years we have invested millions of dollars in R&D to build our platform allowing us to measure cognitive activity via the eye through mobile phones. Through multiple iterations and use cases we are now focused on building the world's first Objective Mental Health Diagnostics on top of our core technology. Our first diagnostic is for PTSD and is entering clinical trials now, followed soon by additional indications for Anxiety and Depression. As the world struggles with a mental health crisis, it is not hyperbolic to suggest that an objective diagnostic platform, that gives clinicians a safe and objective accurate approach to identifying and monitoring mental health disease, will redefine how mental health services are provided and will enable access to treatment for hundreds of millions of sufferers. The Senseye platform has the potential to be the technology that drives this change.
Role Description
We are seeking a Research Data Analyst to join our team. This is an analysis-first role embedded with our data science and research personnel: you will design, run, and interpret analyses of experimental data across the full lifecycle of a research study. We use AI-assisted tools to help us write analysis code faster and better, but you need a solid grasp of coding and how the code works: as the human in the loop, you have the final say on what gets released and how it is analyzed, and spotting bugs and subtle mistakes is far easier for someone who genuinely understands the code than for someone who relies entirely on AI. You will co-create hypotheses with our senior scientists, own the execution of analyses, and provide the initial interpretation of results: the experimental logic, their validity, and what they actually mean. The signals we work with are small, so every detail matters. The ideal candidate is passionate about being part of an innovative research team, detail-oriented, adaptable, and motivated to grow. You will collaborate with our Research and Data Scientists and be involved in many aspects of our work, from experiment design through analysis and reporting.
Responsibilities
  • Plan and execute analyses of experimental data with support from our research and data science team: co-develop a clear hypothesis, specify expected outcomes, and select appropriate statistical methods before running the analysis.
  • Use Python and AI-assisted coding tools to build analysis pipelines and statistical tests, critically reviewing generated code for correctness.
  • Validate results end to end: check data quality, verify assumptions, spot anomalies and subtle errors, and trace unexpected results to their root cause.
  • Interpret findings in the context of the experimental design, and be clear about what the results do and do not support.
  • Present results of analyses to team members on an ongoing basis.
  • Write clear, well-organized analysis reports documenting methods, results, and interpretation.
  • Prepare, maintain, and update technical documentation.
  • Attend weekly project meetings and collaborate closely with data science and research team members through study design, execution, analysis, and interpretation.
  • Other duties and responsibilities may be assigned by research supervisors.

Requirements
  • Bachelor's degree in Neuroscience, Psychology, Computer Science, Statistics, Data Science, or a related quantitative or bioscience field.
  • Working proficiency in Python and scientific computing libraries (e.g., NumPy, Pandas, Matplotlib) for data analysis and statistical work.
  • A solid understanding of the research workflow: experimental design, hypothesis formulation, execution, analysis, and interpretation of results.
  • The ability to critically evaluate analysis code and outputs - catching small errors matters, because the effects we measure are small.
  • Strong attention to detail and a root-cause mindset: you don't stop at "this looks wrong" - you dig in and find out why.
  • Clear written communication and the ability to produce readable reports of methods and findings.
  • Motivation to learn and improve. You don't need to be an expert in any one field, but you should be eager to build on your skills.
  • An outside-the-box mindset: we don't need a robot - we want someone willing to take risks, try new approaches, and push an analysis beyond what an AI prompt hands back, because you care to understand what's really going on.
Nice to Have
  • Master's degree in Computer Science, Statistics, Data Science, Neuroscience, Psychology, or a related field.
  • Laboratory or human subjects research experience (academic lab, thesis project, internship, or publication).
  • Experience with research statistics (e.g., parametric, nonparametric, or Bayesian statistics).
  • Experience using AI coding assistants effectively - prompting, reviewing, and correcting generated code.
  • Experience preparing manuscripts for publication.

Benefits
  • The freedom and trust to define your role as we design, build, and ship our products
  • Competitive salary and stock option plan
  • Flexible paid time off (vacation, sick leave, and public holidays)
  • Flexible schedules
  • Company health care plan
    • Medical, dental, and vision insurance
    • Short and long term disability insurance
    • Life insurance policy
  • 401k
  • Commuter benefits for parking, public transit, carshares, etc.
  • Mothers' room
  • Fully stocked kitchen
  • Opportunities for continuing education

The compensation for this role is $65,000-$80,000 annually.
Senseye is dedicated to building a community of employees that are diverse, passionate, and engaged. We are committed to equal opportunity regardless of race, color, ancestry, religion, gender, gender identity, parental or pregnancy status, national origin, sexual orientation, age, marital status, disability, or veteran status. When we're safe, healthy, and balanced we can accomplish phenomenal things together.

Senseye logo

About Senseye

Sourced by ZipRecruiter

Industry

Scientific research and development services

Company size

11 - 50 Employees

Headquarters location

Austin, TX, US

Year founded

2015

Social media