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Probability Theory Jobs in California (NOW HIRING)

Swish Analytics

NFL Data Scientist

San Francisco, CA · On-site +1

$140K/yr

Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods * 5+ years of demonstrated experience developing and delivering ...

Roku

Senior Machine Learning Engineer

San Jose, CA

$229K - $367K/yr

Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning using both general-purpose software and ...

Swish Analytics

Soccer Data Scientist

San Francisco, CA · On-site +1

$130K/yr

Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods * 5+ years of demonstrated experience developing and delivering ...

Swish Analytics

Tennis Data Scientist

San Francisco, CA · On-site +1

$135K - $190K/yr

Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods * 5+ years of demonstrated experience developing and delivering ...

Raytheon

RF Data Link Engineer II

San Jose, CA · On-site

Probability theory * Stochastic signal processing * RF and electromagnetic theory Qualifications We Prefer * Master's degree in electrical engineering or computer engineering with a focus in digital ...

Swish Analytics

Tennis Data Scientist

San Francisco, CA

$135K - $190K/yr

Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods * 5+ years of demonstrated experience developing and delivering ...

Swish Analytics

NFL Data Scientist

San Francisco, CA

$140K/yr

Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods * 5+ years of demonstrated experience developing and delivering ...

Raytheon

RF Data Link Engineer II

San Diego, CA · On-site

Probability theory * Stochastic signal processing * RF and electromagnetic theory Qualifications We Prefer * Master's degree in electrical engineering or computer engineering with a focus in digital ...

Raytheon

Senior RF Data Link Engineer

San Diego, CA · On-site

Probability theory * Stochastic signal processing * RF and electromagnetic theory Qualifications We Prefer * Master's degree in electrical or computer engineering with a focus in digital ...

Raytheon

Senior RF Data Link Engineer

San Jose, CA · On-site

Probability theory * Stochastic signal processing * RF and electromagnetic theory Qualifications We Prefer * Master's degree in electrical or computer engineering with a focus in digital ...

Raytheon

RF Data Link Engineer II

Los Angeles, CA · On-site

Probability theory * Stochastic signal processing * RF and electromagnetic theory Qualifications We Prefer * Master's degree in electrical engineering or computer engineering with a focus in digital ...

Raytheon

Principal RF Data Link Engineer

San Jose, CA · On-site

Probability theory * Stochastic signal processing * RF and electromagnetic theory Qualifications We Prefer * Master's degree in electrical engineering or computer engineering with a focus on digital ...

Swish Analytics

Data Scientist

San Francisco, CA · Remote

$150K/yr

Experience in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods. * Excellent analytical and problem-solving ability, and a ...

Swish Analytics

Data Scientist

San Francisco, CA · On-site +1

$150K/yr

Experience in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods. * Excellent analytical and problem-solving ability, and a ...

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Probability Theory information

What is probability theory?

Probability theory is a branch of mathematics that deals with the analysis of random phenomena and the likelihood of different outcomes. It provides a mathematical framework for quantifying uncertainty, modeling random events, and making predictions about future occurrences. Probability theory is widely used in fields such as statistics, finance, engineering, and science to analyze data, assess risks, and inform decision-making.

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

To thrive as a Probability Theorist, you typically need a strong background in advanced mathematics, including calculus, linear algebra, and mathematical statistics, supported by at least a master's or Ph.D. in mathematics or a related field. Familiarity with mathematical software such as MATLAB, R, or Python, and experience with statistical computing tools, are commonly required. Analytical thinking, attention to detail, and effective problem-solving abilities are crucial soft skills in this field. These competencies enable rigorous analysis, innovative research, and practical applications of probability theory in diverse scientific and engineering domains.

What are some common challenges faced by professionals working in the field of probability theory?

Professionals in probability theory often encounter challenges such as translating abstract mathematical concepts into practical applications, especially when collaborating with colleagues from other disciplines like engineering, finance, or data science. The work can also involve tackling complex, open-ended problems that require creative solutions and rigorous proof techniques. Additionally, staying current with rapidly evolving research and methodologies is crucial, as the field is continually influenced by advances in related areas like machine learning and statistics. Effective communication and teamwork are essential, particularly when conveying complex ideas to non-specialists or integrating probability models into larger projects.

What is the difference between Probability Theory vs Data Analyst?

AspectProbability TheoryData Analyst
Required CredentialsMathematics or Statistics degree, advanced certificationsBachelor's in Statistics, Data Science, or related field
Work EnvironmentTheoretical research, academia, or R&D departmentsBusiness settings, tech companies, or consulting firms
Industry UsageModeling, risk assessment, researchData interpretation, reporting, decision support
Common Search/ComparisonFocus on mathematical foundationsFocus on practical data analysis skills

Probability Theory involves the mathematical study of randomness and uncertainty, often used in research and modeling. Data Analysts apply statistical methods to interpret data and support business decisions. While Probability Theory provides the theoretical foundation, Data Analysts focus on practical data handling and reporting.

What are the careers in probability theory?

Careers in probability theory include roles such as data analyst, statistician, quantitative analyst, risk analyst, and research scientist. These positions often require strong mathematical skills, proficiency with statistical software, and a solid understanding of stochastic processes and modeling techniques.

What are three career fields that use probability theory?

Probability theory is fundamental in fields such as finance, where it underpins risk assessment and modeling; data science and machine learning, which rely on statistical methods to analyze data; and engineering, particularly in areas like reliability analysis and quality control. Professionals in these fields often use statistical software and require strong analytical skills.

What are popular job titles related to Probability Theory jobs in California?

For Probability Theory jobs in California, the most frequently searched job titles are:

What job categories do people searching Probability Theory jobs in California look for?

The top searched job categories for Probability Theory jobs in California are:

What cities in California are hiring for Probability Theory jobs?

Cities in California with the most Probability Theory job openings:

Probability Theory jobs near you
Infographic showing various Probability Theory job openings in California as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 79% Physical, 1% Hybrid, and 20% Remote job distribution.

NFL Data Scientist

Swish Analytics

San Francisco, CA • On-site, Remote

$140K/yr

Full-time

Re-posted 29 days ago

Job description

Company Description
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
Job Description
Swish Analytics is looking for an NFL Data Scientists to join our ever-growing team! Data Science is at the core of our business, so this team has true ownership and impact over developing core components of Swish's data products. This position is remote from the USA.
Duties:
  • Ideate, develop and improve machine learning and statistical models that drive Swish's core algorithms for producing state-of-the-art sports betting products.
  • Develop contextualized feature sets using sports specific domain knowledge.
  • Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with data engineering and product teams to deploy new models.
  • Strive to constantly improve model performance using insights from rigorous offline and online experimentation.
  • Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts.
  • Adhere to software engineering best practices and contribute to shared code repositories.
  • Document modeling work and present to stakeholders and other technical and non-technical partners.

Requirements:
  • Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area
  • Demonstrated experience developing models at production scale for NFL, CFB, or sports betting for 2+ years
  • Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
  • 5+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs in sports or sports betting
  • Experience with relational SQL & Python
  • Experience with source control tools such as GitHub and related CI/CD processes
  • Experience working in AWS environments etc
  • Proven track record of strong leadership skills. Has shown ability to partner with teams in solving complex problems by taking a broad perspective to identify innovative solutions
  • Excellent communication skills to both technical and non-technical audiences

Base salary: Starting at $140,000
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Data Science Role NFL Team Locations San Francisco, CA - Remote Remote status Fully Remote

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