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Probabilistic Programming Bayesian Jobs in California

Avathon

Senior AI Scientist - Planning

Pleasanton, CA

$160K - $240K/yr

Familiarity with probabilistic programming or Bayesian methods for demand sensing * Experience with cloud ML infrastructure (AWS SageMaker, GCP Vertex, or equivalent) * Domain experience in energy ...

Avathon

Senior AI Scientist - Planning

Pleasanton, CA · On-site

Familiarity with probabilistic programming or Bayesian methods for demand sensing * Experience with cloud ML infrastructure (AWS SageMaker, GCP Vertex, or equivalent) * Domain experience in energy ...

Yum Brands

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

Experience with Bayesian or probabilistic modeling frameworks such as PyMC or ArviZ. * Familiarity ... Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field ...

Snowflake

Senior Data Scientist

Menlo Park, CA · On-site

... probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches ... Engineering, Computer Science) or equivalent practical experience. • 8+ years of experience ...

General Atomics

Engineer VII

Poway, CA · On-site

$128K - $229K/yr

We have an exciting opportunity for a Project Engineer integrated product team (IPT) leader to join ... Strong background in probabilistic methods (e.g., Bayesian inference, filtering, estimation theory)

Pop-Up Talent

Senior Research Engineer

Santa Clara, CA · On-site

$200K/yr

Develop probabilistic models that quantify uncertainty and confidence in location estimates ... Formulate and solve complex inference problems using Bayesian estimation, filtering, optimization ...

New

Kodiak

Autonomy Systems Software Engineer

San Francisco, CA · On-site

$203K - $241K/yr

Strong programming skills in Python, MATLAB, C++, or C * Hands-on work across multiple of the ... Bayesian inference (e.g., beta and gamma distributions) * Markov models and probabilistic system ...

Yum

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning ... Experience with Bayesian or probabilistic modeling frameworks such as PyMC or ArviZ. * Familiarity ...

ASM Global

Manger, Modeling Insights

Los Angeles, CA · On-site

$90K - $100K/yr

ApplyBayesian and probabilistic methodsto quantify uncertainty and improve decision-making ... Perform feature engineering, model evaluation, and impact measurement, clearly communicating ...

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Probabilistic Programming Bayesian information

What are the typical challenges faced by professionals working in Probabilistic Programming with a Bayesian focus, and how can they be addressed?

Professionals working in Probabilistic Programming with a Bayesian focus often encounter challenges related to model complexity, computational efficiency, and communicating results to non-technical stakeholders. Building accurate Bayesian models requires careful selection of priors and an understanding of underlying data distributions, which can be demanding without robust domain expertise. Additionally, computational demands can be high, especially for large datasets or complex hierarchical models, making efficient sampling and approximation methods essential. Collaborating closely with domain experts and leveraging modern probabilistic programming frameworks can help address these challenges and ensure practical, interpretable results.

What is probabilistic programming in the context of Bayesian statistics?

Probabilistic programming in the context of Bayesian statistics refers to writing computer programs that use probability distributions and Bayesian inference to model uncertainty and learn from data. These programs allow users to define complex probabilistic models using code, making it easier to specify, fit, and analyze Bayesian models. Probabilistic programming languages, such as Stan, PyMC, or Edward, provide tools to automate inference, enabling practitioners to focus on modeling rather than mathematical derivations. This approach is widely used in fields like machine learning, data science, and scientific research to handle uncertainty and make predictions.

What is the difference between Probabilistic Programming Bayesian vs Data Scientist?

AspectProbabilistic Programming BayesianData Scientist
Required credentialsBackground in statistics, probability, programmingStatistics, computer science, or related degree
Work environmentResearch, modeling, algorithm developmentData analysis, visualization, business insights
Industry usageAI, machine learning, research projectsBusiness, finance, tech, healthcare

Probabilistic Programming Bayesian focuses on developing models using Bayesian methods and probabilistic programming languages, often in research or AI development. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles require statistical knowledge, Bayesian programmers specialize in probabilistic modeling, whereas Data Scientists apply a broader set of data analysis techniques.

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

To thrive as a Probabilistic Programming Bayesian specialist, you need a strong background in statistics, probability theory, and Bayesian inference, often supported by a degree in mathematics, statistics, computer science, or a related field. Expertise with probabilistic programming languages (such as Stan, PyMC, or TensorFlow Probability) and familiarity with statistical modeling software are also essential. Analytical thinking, problem-solving, and effective communication skills help translate complex models into actionable insights and collaborate with interdisciplinary teams. These skills and qualities are crucial for developing robust, interpretable models that inform decision-making in research and industry applications.
What are popular job titles related to Probabilistic Programming Bayesian jobs in California? For Probabilistic Programming Bayesian jobs in California, the most frequently searched job titles are:
What job categories do people searching Probabilistic Programming Bayesian jobs in California look for? The top searched job categories for Probabilistic Programming Bayesian jobs in California are:
What cities in California are hiring for Probabilistic Programming Bayesian jobs? Cities in California with the most Probabilistic Programming Bayesian job openings:
Probabilistic Programming Bayesian jobs near you
Infographic showing various Probabilistic Programming Bayesian job openings in California as of June 2026, with employment types broken down into 2% As Needed, 8% Full Time, 82% Part Time, 4% Temporary, and 4% Nights. Highlights an 67% Physical, 2% Hybrid, and 31% Remote job distribution.
Postdoctoral Fellow - Modeling Tumor Evolution and Treatment (Hybrid)

Postdoctoral Fellow - Modeling Tumor Evolution and Treatment (Hybrid)

City of Hope

Duarte, CA

$51K - $69K/yr

Full-time

Posted 16 days ago

City Of Hope rating

8.4

Company rating: 8.4 out of 10

Based on 87 frontline employees who took The Breakroom Quiz

18th of 877 rated healthcare providers

Job description

Postdoctoral Research Fellow — Modeling Tumor Evolution and Treatment 

Join the forefront of groundbreaking research at City of Hope where we're changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine through cutting-edge research.

The Bild Laboratory at City of Hope uses systems biology to understand how tumors evolve under therapy, uncover resistance mechanisms, and identify actionable vulnerabilities. We integrate longitudinal patient cohorts with single-cell and bulk multi-omics, liquid biopsy, and patient-derived models, partnering closely with clinicians at an NCI-designated Comprehensive Cancer Center.

We are seeking a Postdoctoral Research Fellow to lead computational projects at the interface of tumor evolution, liquid biopsy, and machine learning. The successful candidate will develop and apply methods that integrate multimodal molecular and clinical data (genomic, epigenomic, transcriptomic) across serial patient timepoints to model tumor population dynamics during treatment and predict clinical outcomes. This is a highly collaborative, translational role for a scientist who wants to connect methods development with impactful questions in cancer biology.

Learn more about Dr. Bild’s lab here.

As a successful candidate you will:

  • Build probabilistic models of tumor dynamics from serial ctDNA and tissue samples.

  • Develop deep learning frameworks that integrate multimodal data to predict therapeutic response.

  • Construct scalable pipelines for analyzing large longitudinal genomic cohorts.

  • Validate computationally derived biomarkers in collaboration with experimental and clinical teams.

  • Publish in high-impact journals and present at major conferences.

  • Mentor junior lab members.

  • Develop an independent research direction that positions you for a faculty or senior industry role.

Your qualifications should include:

  • A PhD (or equivalent) in computational biology, bioinformatics, systems biology, biomedical engineering, statistics, computer science, or a closely related quantitative field.

Demonstrated expertise across most of the following areas:

Cancer biology domain knowledge

  • Working understanding of tumor evolution and clonal dynamics, pathway and signaling biology in the context of the hallmarks of cancer, and the molecular biology connecting DNA mutation and methylation to RNA and protein function.

  • Familiarity with liquid biopsy modalities (ctDNA, cfDNA methylation, CTCs) and their clinical applications, along with awareness of oncology biomarker validation frameworks, is strongly preferred.

Computational and machine learning skills

  • Proficiency in large-scale genomic data management and bioinformatic processing, including fluency with R/Bioconductor workflows and Python scientific stacks.

  • Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow, and ideally with probabilistic programming tools such as Pyro or Stan.

  • Experience with multimodal data fusion and building efficient, scalable data pipelines for large genomic datasets.

Statistics and mathematics

  • Strong grounding in multivariate statistics, dimensionality reduction, and latent variable modeling.

  • Experience with temporal or dynamical modeling, Bayesian inference, and survival analysis for clinical outcome data.

Scholarly record and collaboration

  • A track record of first-author peer-reviewed publications (or preprints) appropriate to career stage, and the communication skills to work effectively across a team that spans multiple disciplines.  

City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location.

City of Hope is an equal opportunity employer.

To learn more about our Comprehensive Benefits, please CLICK HERE.

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About City of Hope

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City of Hope is an independent biomedical research and treatment organization for cancer, diabetes and other life-threatening diseases. Founded in 1913, City of Hope is a leader in bone marrow transplantation and immunotherapy such as CAR T cell therapy. City of Hopes translational research and personalized treatment protocols advance care throughout the world. Human synthetic insulin, monoclonal antibodies and numerous breakthrough cancer drugs are based on technology developed at the institution. AccessHope, a subsidiary launched in 2019 serves employers and their health care partners by providing access to City of Hopes specialized cancer expertise. City of Hope is ranked among the nations Best Hospitals in cancer by U.S. News & World Report and received Magnet Recognition from the American Nurses Credentialing Center. Its main campus is located near Los Angeles, with additional locations throughout Southern California and in Arizona.

Industry

Hospitals

Company size

1,001 - 5,000 Employees

Headquarters location

Duarte, CA, US

Year founded

1913

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