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Postdoctoral In Bayesian Statistics Jobs in California

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

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 ...

NVIDIA AI

Senior Data Scientist - Finance

Santa Clara, CA · On-site

... and driving innovation in financial data science initiatives. Responsibilities : • Combine ... Bayesian statistics, simulation, and optimization. • Integrate AI tools and Agents into data ...

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Postdoctoral In Bayesian Statistics information

What is a Postdoctoral position in Bayesian Statistics?

A Postdoctoral position in Bayesian Statistics is a research-focused role for individuals who have recently completed their PhD in statistics, mathematics, or a related field. These positions involve conducting advanced research using Bayesian methods, which apply probability to infer statistical conclusions. Postdocs often work on developing new Bayesian models, collaborating on interdisciplinary projects, and publishing research findings. Such positions are typically temporary and designed to further prepare researchers for academic, industry, or governmental roles.

What are some common challenges faced by postdoctoral researchers in Bayesian statistics, and how can they be addressed?

Postdoctoral researchers in Bayesian statistics often encounter challenges such as managing complex, high-dimensional data, staying current with rapidly evolving computational methods, and balancing independent research with collaborative projects. Effective strategies include leveraging open-source statistical software, actively participating in seminars and workshops to stay updated, and establishing regular communication with interdisciplinary teams. Building a strong professional network and seeking mentorship within the department can also help in navigating research obstacles and advancing one's career.

What is the difference between Postdoctoral In Bayesian Statistics vs Postdoctoral In Data Science?

AspectPostdoctoral In Bayesian StatisticsPostdoctoral In Data Science
Required CredentialsPhD in Statistics, Mathematics, or related fieldPhD in Computer Science, Statistics, or related field
Work EnvironmentAcademic research, university labsResearch institutions, tech companies, industry labs
Employer & Industry UsageUniversities, research institutesTech firms, finance, healthcare, consulting
Common Search & Comparison IntentSpecialized research roles in Bayesian methodsBroader data analysis and machine learning roles

Postdoctoral In Bayesian Statistics focuses on advanced research in Bayesian methods within academic settings, requiring deep statistical expertise. In contrast, Postdoctoral In Data Science covers a broader range of data analysis techniques, including machine learning, often in industry environments. Both roles require a PhD but differ in application focus and work environment.

What are the key skills and qualifications needed to thrive as a Postdoctoral Researcher in Bayesian Statistics, and why are they important?

To thrive as a Postdoctoral Researcher in Bayesian Statistics, you need an advanced degree (typically a PhD) in statistics or a related field, with strong expertise in Bayesian inference and probabilistic modeling. Proficiency with statistical programming languages such as R, Python, or Stan, and experience with specialized Bayesian analysis software are highly valued. Excellent problem-solving skills, collaboration, and the ability to communicate complex statistical concepts clearly are standout soft skills for this role. These skills and qualities are crucial for conducting rigorous research, publishing impactful results, and contributing effectively to scientific teams.
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Postdoctoral In Bayesian Statistics jobs near you
Tennis Data Scientist

Tennis Data Scientist

Swish Analytics

San Francisco, CA

$135K - $190K/yr

Full-time

Re-posted 18 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 a Tennis 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 Tennis 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: $135,000 - $190,000

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.

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