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Internship Bayesian Jobs (NOW HIRING)

Costello Medical

Senior Statistician

Boston, MA · On-site

$100K/yr

... 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 ...

Costello Medical

Senior Statistician

Boston, MA

$100K/yr

... 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 ...

Costello Medical

Senior Statistician

New York, NY · On-site

$100K/yr

... 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 ...

Costello Medical

Senior Statistician

New York, NY

$100K/yr

... 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 ...

Costello Medical

Senior Statistician

Boston, MA · On-site

$100K/yr

... 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 ...

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Internship Bayesian information

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How much do internship bayesian jobs pay per hour?

As of Jun 21, 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:
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Internship Bayesian jobs near you
Infographic showing various Internship Bayesian job openings in the United States as of June 2026, with employment types broken down into 9% As Needed, 4% Full Time, and 87% Part Time. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.
Associate Director/Principal, Machine Learning Scientist

Associate Director/Principal, Machine Learning Scientist

BigHat Biosciences

San Mateo, CA

$254K - $290K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 3 days ago

Job description

Description
The role: We are seeking a creative, accomplished Assoc. Director or Principal Machine Learning Scientist to advance the state of the art in ML-driven therapeutic antibody design.

At BigHat Biosciences our full-stack antibody drug development platform uses ML to drive every stage from discovery to optimization. Our roboticized high-throughput wet-lab continually adds to our large proprietary datasets, which are piped through a custom LIMS++ data management and orchestration layer to automatically update and deploy the latest models. This makes the development of complex, next-gen therapeutics ‘trivially parallelizable’, at a pace which only accelerates as we develop better ML tooling.

You’re not interested in just git-cloning the latest NeurIPS pub and swapping out the dataset. Motivated by an enthusiasm for the possibility of addressing unmet patient needs and a curiosity about the underlying biology, you’ll apply your world-class ML skillset to refine and expand this state-of-the-art protein engineering platform. Success will mean not only hands-on methods development, but helping shape the direction for future ML research, and actively participating in the application of our platform to the accelerated design of new therapeutics.

Key Responsibilities
  • Design and implement the next state-of-the-art generative models of antibody sequence and structure, and predictive models of antibody properties, trained on proprietary internal datasets of thousands to millions of antibodies.
  • Provide leadership, technical guidance, and mentorship to other ML and data science FTEs and interns.
  • Help set strategy for future ML research, driven by a strong high-level understanding of BigHat programs and operations as well as real-world drug development challenges.
  • Develop, refine, and deploy de novo design methods for generating initial hits to challenging, therapeutically interesting targets.
  • Develop multi-modality, multi-objective iterative protein sequence optimization approaches to lab-in-the-loop antibody design problems for validation and deployment in our high-throughput wet lab - at BigHat success is only declared upon synthesis of real antibodies with drug-like properties.
  • Maintain an in-depth understanding of the current state-of-the-art in ML-driven protein engineering, both in the literature and at BigHat.
  • Share your findings at top-tier conferences and publish in leading scientific journals to advance the field of protein engineering.
  • Provide ML expertise and support for ongoing therapeutics programs, directly contributing to the development of new drugs.
  • Collaborate with our engineering team to ensure maximal efficiency in the automated and agentic deployment of our latest models to our therapeutics programs.
  • Work closely with an interdisciplinary team of drug developers, wet lab scientists, automation specialists, data scientists, etc. to identify inefficiencies or potential improvements in BigHat’s platform, and plan and prioritize ML methods development accordingly.

Skills Knowledge and Expertise
  • PhD in ML/CS or in the hard sciences with 5+ years experience post-graduation in developing and applying novel ML methods, and a strong quantitative background.
  • Publications in major ML conferences and/or leading journals, and an extensive demonstrable track record developing and applying novel ML in industry.
  • Strong competency in Python, familiarity with PyTorch, and experience with modern software engineering best practices.
  • Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams.
  • Enjoys a fast-paced environment and excels at executing across multiple projects.
  • Familiarity with the current state-of-the-art in ML-driven protein engineering
  • Nice-to-haves include experience with de novo design, NGS data, Bayesian optimization, familiarity with antibody biology and drug development, and experience training and deploying models on AWS.

Total Rewards
The salary estimated for this position is $254,000 - $290,000 + bonus + options + benefits. Compensation will vary depending on job-related knowledge, skills, and experience. Actual compensation will be confirmed in writing at the time of the offer.
What BigHat Offers:
  • Range of health insurance plan options through Anthem and Kaiser (monthly credit if benefit waived)
  • Dental, and vision coverage through Guardian
  • Additional well-being benefits through Nayya, OneMedical, Wagmo, Rula, and more
  • 401(k) with company match 
  • DTO, two weeks of company-wide shutdown, and 12 company holidays
  • Paid parental leave