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Remote Bayesian Jobs in California (NOW HIRING)

Data Scientist

San Francisco, CA · Remote

$160K - $200K/yr

This is a remote position, but we do have an office in San Fransisco. You will be the first data ... Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization ...

Data Scientist

San Francisco, CA · On-site +1

$160K - $200K/yr

This is a remote position, but we do have an office in San Fransisco. You will be the first data ... Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization ...

This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ... Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics ...

Tennis Data Scientist

San Francisco, CA · On-site +1

$135K - $190K/yr

This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ... Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics ...

Data Scientist

Santa Clara, CA · On-site +1

$130K - $150K/yr

Santa Clara, CA (preferred) or Remote - US-based Job Term: Full-Time The Opportunity Picarro ... Apply statistical techniques such as Bayesian inference, hypothesis testing, and Monte Carlo ...

Data Scientist

San Francisco, CA · On-site +1

$150K/yr

This position is remote from the USA or Canada. Duties: * Develop infrastructure for trader ... Experience in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics ...

Explainable AI Engineer

Palo Alto, CA · Remote

$122K - $165K/yr

Bayesian statistics * Monte Carlo analysis * Mathematical optimization * Decision and Control ... This is a remote position. USA, Nationwide. * You will have an opportunity to start as a contractor ...

Decision Scientist II, Mobile

Santa Monica, CA · On-site +1

$130K - $155K/yr

... Bayesian inference * Experience in product analytics with a focus on mobile apps or building zero ... Employer-matched 401(k) plan #LI-Remote The US base salary range for this full-time position is ...

This position is remote from the USA or Canada. Duties: * Develop infrastructure for trader ... Experience in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics ...

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Remote Bayesian information

What is a Remote Bayesian?

A Remote Bayesian is a professional who specializes in Bayesian statistics and probabilistic modeling while working remotely, often in fields like data science, machine learning, or research. They use Bayesian methods to update probabilities and make predictions based on data, collaborating with teams through digital communication tools. Remote Bayesians may work for tech companies, research institutions, or as independent consultants, applying their expertise to solve complex problems without being tied to a physical office location.

How do Remote Bayesian professionals typically collaborate with cross-functional teams given the virtual nature of their work?

Remote Bayesian professionals often work closely with data scientists, engineers, and decision-makers through virtual collaboration tools such as video conferencing, shared code repositories, and project management platforms. Clear communication is key, as they must explain complex probabilistic models and inferences to both technical and non-technical stakeholders. Regular check-ins and documentation help ensure alignment on project goals, data requirements, and model outcomes. This collaborative dynamic fosters an environment where insights from Bayesian analysis can directly inform business or research decisions, despite the physical distance.

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

To thrive as a Remote Bayesian, you need strong statistical knowledge, expertise in Bayesian inference, and a background in mathematics or data science, often supported by an advanced degree. Familiarity with programming languages like Python or R, Bayesian software such as Stan or PyMC, and experience with remote collaboration tools are typically required. Critical thinking, problem-solving, and clear communication are essential soft skills for interpreting results and working with distributed teams. These abilities are vital for delivering accurate, actionable insights in a remote environment where clear analysis and collaboration drive project success.

What is the difference between Remote Bayesian vs Remote Data Scientist?

AspectRemote BayesianRemote Data Scientist
Required CredentialsBackground in statistics, Bayesian methods, programming (Python/R)Statistics, computer science, or related degree; programming skills
Work EnvironmentResearch-focused, analytical tasks, often in tech or financeData analysis, modeling, business insights across industries
Industry UsageResearch institutions, AI, machine learning, financeTech companies, consulting, finance, healthcare

Remote Bayesian specialists focus on Bayesian statistical methods and probabilistic modeling, often in research or AI contexts. Remote Data Scientists have broader roles in data analysis and modeling across various industries. While both roles require strong analytical skills and programming, Remote Bayesian roles emphasize Bayesian techniques, whereas Remote Data Scientist roles encompass a wider range of data analysis tasks.

What cities in California are hiring for Remote Bayesian jobs?

Cities in California with the most Remote Bayesian job openings:

Infographic showing various Remote Bayesian job openings in California as of September 2026, with employment types broken down into 1% Internship, 77% Full Time, 21% Part Time, and 1% Contract. Highlights an 62% Physical, 2% Hybrid, and 36% Remote job distribution.

Postdoc: Millimeter-Wave Cloud Radar Remote Sensing

Pasadena, CA • On-site, Remote

JPL
Marketing • 51 - 200 employees

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 13 days ago


Job description

Job Details
New ideas are all around us, but only a few will change the world. That's our focus at JPL. We ask the biggest questions, then search the universe for answers-literally. We build upon ideas that have guided generations, then share our discoveries to inspire generations to come. Your mission-your opportunity-is to seek out the answers that bring us one step closer. If you're driven to discover, create, and inspire something that lasts a lifetime and beyond, you're ready for JPL.
Located in Pasadena, California, JPL has a campus-like environment situated on 177 acres in the foothills of the San Gabriel Mountains and offers a work environment unlike any other: we inspire passion, foster innovation, build collaboration, and reward excellence.
The postdoc will develop and apply advanced retrieval algorithms to improve the understanding of cloud microphysical properties using ground-based, airborne, and future spaceborne radar observations. Research will include the application of Bayesian inverse methods, cloud microphysics modeling, and quantitative analysis of large atmospheric datasets to advance remote sensing capabilities and support next-generation Earth science missions.
The successful candidate will also participate in the analysis of observations from field campaigns, including the North American Upstream Feature-Resolving and Tropopause Uncertainty Reconnaissance Experiment (NURTURE) and Clouds And Precipitation Experiment at kennaook (CAPE-k) campaigns, and help prepare the scientific foundation for future multi-frequency cloud radar missions.
Responsibilities
  • Conduct research in cloud microphysics and atmospheric remote sensing.
  • Develop and implement retrieval algorithms for millimeter-wave cloud radar observations using Bayesian inverse methods.
  • Analyze G-band CloudCube and other multi-frequency cloud radar datasets.
  • Process, analyze, and interpret large atmospheric and remote sensing datasets using Python and scientific computing tools.
  • Publish research results in peer-reviewed journals and present results at scientific conferences.
  • Collaborate with multidisciplinary teams to advance future radar remote sensing technologies.

Required Qualifications
  • Ph.D. in Atmospheric Science, Earth Science, Remote Sensing, or a closely related field.
  • Research experience in atmospheric physics, cloud microphysics, or radar remote sensing.
  • Experience developing or applying remote sensing retrieval algorithms.
  • Proficiency in Python and scientific data analysis.
  • Experience working with large observational or model datasets.
  • Demonstrated record of peer-reviewed scientific publications.

The appointee will carry out research in collaboration with JPL advisor, resulting in publications in the open literature.
Applicants may be subject to additional program requirements by NASA. Postdoc positions are awarded for a minimum of one-year period and may be renewed up to a maximum of three years. Candidates should submit the following to this site: CV, representative publications, contact information for three references, and a cover letter stating their research accomplishments and interests.
JPL has a catalog of benefits and perks that span from the traditional to the unique. This includes a variety of health, dental, vision, wellbeing, and retirement plans, paid time off, learning, rideshare, childcare, flexible schedule, parental leave and many more. Our focus is on work-life balance, and living healthy, fulfilling lives as we Dare Mighty Things Together. For benefits eligible positions, benefits are effective the first day of the month coincident with or immediately following the employee's start date.
For further benefits information click Benefits and Perks
The hiring range displayed below is specifically for those who will work in or reside in the location listed. In extending an offer, Jet Propulsion Laboratory considers factors including, but not limited to, the candidate's job related skills, experience, knowledge, and relevant education/training.
The typical full time equivalent annual hiring range for this job in Pasadena, California.
$83,820 - $83,820
JPL is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, citizenship, ancestry, age, marital status, physical or mental disability, medical condition, genetic information, pregnancy or perceived pregnancy, gender, gender identity, gender expression, sexual orientation, protected military or veteran status or any other characteristic or condition protected by Federal, state or local law.
In addition, JPL is a VEVRAA Federal Contractor.
EEO is the Law.
EEO is the Law Supplement
Pay Transparency Nondiscrimination Provision
The Jet Propulsion Laboratory is a federal facility. Due to rules imposed by NASA, JPL will not accept applications from citizens of designated countries or those born in a designated country unless they are U.S. Citizens, Legal Permanent Residents of the U.S or have other protected status under 8 U.S.C. 1324b(a)(3). The Designated Countries List is available here.