... e.g., bayesian pooling, hierarchical modeling) * Demonstrated communication skills and experience presenting complex findings to both technical and non-technical stakeholders * Demonstrated ...
... e.g., bayesian pooling, hierarchical modeling) * Demonstrated communication skills and experience presenting complex findings to both technical and non-technical stakeholders * Demonstrated ...
... e.g., bayesian pooling, hierarchical modeling) * Demonstrated communication skills and experience presenting complex findings to both technical and non-technical stakeholders * Demonstrated ...
... e.g., bayesian pooling, hierarchical modeling) * Demonstrated communication skills and experience presenting complex findings to both technical and non-technical stakeholders * Demonstrated ...
Director, AI Enabled Discovery and Digital R&D
San Jose, CA · On-site
$200K - $300K/yr
... models and autonomous experimentation connecting EMD Electronics' capabilities to the businesses of ... Extend Bayesian optimization capabilities to new material systems and R&D domains; deepen ...
Director, AI Enabled Discovery and Digital R&D
San Jose, CA · On-site
$200K - $300K/yr
... models and autonomous experimentation connecting EMD Electronics' capabilities to the businesses of ... Extend Bayesian optimization capabilities to new material systems and R&D domains; deepen ...
Senior ML Engineer, LLM / VLM Distillation
Mountain View, CA · Hybrid
$123K - $169K/yr
AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust ...
Senior ML Engineer, LLM / VLM Distillation
Mountain View, CA · Hybrid
$123K - $169K/yr
AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust ...
Extensive data modeling and data architecture skills. * Advanced math skills (linear algebra, Bayesian statistics, group theory). * Ability to consistently exercise independent discretion and ...
Extensive data modeling and data architecture skills. * Advanced math skills (linear algebra, Bayesian statistics, group theory). * Ability to consistently exercise independent discretion and ...
Strong modeling and experimentation skills (Python, SQL, Bayesian / probabilistic modeling). * Comfort operating with limited data - capable of building and validating proxy-based models. * Blend of ...
Strong modeling and experimentation skills (Python, SQL, Bayesian / probabilistic modeling). * Comfort operating with limited data - capable of building and validating proxy-based models. * Blend of ...
Data Scientist
Mountain View, CA · On-site
Collaborates with stakeholders to define success criteria and align model metrics with business ... Deep knowledge of ML paradigms (supervised/unsupervised learning, reinforcement learning, Bayesian ...
Data Scientist
Mountain View, CA · On-site
Collaborates with stakeholders to define success criteria and align model metrics with business ... Deep knowledge of ML paradigms (supervised/unsupervised learning, reinforcement learning, Bayesian ...
Research Scientist, RL for Autonomous Planning & World Modeling
Mountain View, CA · On-site
$204K - $259K/yr
AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust ...
Research Scientist, RL for Autonomous Planning & World Modeling
Mountain View, CA · On-site
$204K - $259K/yr
AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust ...
Sr. Analyst, Product Analytics
San Mateo, CA · Hybrid
$175K - $248K/yr
... Series, Bayesian Structural Time Series models, Seasonal-Trend Decomposition, and Rolling Regression; building and maintaining dashboards using Tableau/DOMO to integrate ETL processes ...
Sr. Analyst, Product Analytics
San Mateo, CA · Hybrid
$175K - $248K/yr
... Series, Bayesian Structural Time Series models, Seasonal-Trend Decomposition, and Rolling Regression; building and maintaining dashboards using Tableau/DOMO to integrate ETL processes ...
Associate Specialist
San Francisco, CA · On-site
Critical aspects of the research include: (1) Designing and executing methods to integrate data from different sources, including developing a Bayesian Hierarchical Modeling framework; (2) using ...
Associate Specialist
San Francisco, CA · On-site
Critical aspects of the research include: (1) Designing and executing methods to integrate data from different sources, including developing a Bayesian Hierarchical Modeling framework; (2) using ...
Sr. Analyst, Product Analytics
San Mateo, CA · On-site
$175K - $248K/yr
... Series, Bayesian Structural Time Series models, Seasonal-Trend Decomposition, and Rolling Regression; building and maintaining dashboards using Tableau/DOMO to integrate ETL processes ...
Sr. Analyst, Product Analytics
San Mateo, CA · On-site
$175K - $248K/yr
... Series, Bayesian Structural Time Series models, Seasonal-Trend Decomposition, and Rolling Regression; building and maintaining dashboards using Tableau/DOMO to integrate ETL processes ...
Proven experience with Bayesian statistics, applying methods such as Bayesian GBLUP, hierarchical models, and clustering using MCMC or variational inference. * Familiarity with decision theory and ...
Proven experience with Bayesian statistics, applying methods such as Bayesian GBLUP, hierarchical models, and clustering using MCMC or variational inference. * Familiarity with decision theory and ...
Quantitative Geneticist
San Francisco, CA · On-site +1
Proven experience with Bayesian statistics, applying methods such as Bayesian GBLUP, hierarchical models, and clustering using MCMC or variational inference. * Familiarity with decision theory and ...
Quick apply
Quantitative Geneticist
San Francisco, CA · On-site +1
Proven experience with Bayesian statistics, applying methods such as Bayesian GBLUP, hierarchical models, and clustering using MCMC or variational inference. * Familiarity with decision theory and ...
Quantitative Geneticist
South San Francisco, CA · On-site +1
Proven experience with Bayesian statistics, applying methods such as Bayesian GBLUP, hierarchical models, and clustering using MCMC or variational inference. * Familiarity with decision theory and ...
Quantitative Geneticist
South San Francisco, CA · On-site +1
Proven experience with Bayesian statistics, applying methods such as Bayesian GBLUP, hierarchical models, and clustering using MCMC or variational inference. * Familiarity with decision theory and ...
Data Scientist
San Francisco, CA · Remote
$160K - $200K/yr
... with model deployment, monitoring and version control * Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization), either PhD or Advanced MS degree.
Data Scientist
San Francisco, CA · Remote
$160K - $200K/yr
... with model deployment, monitoring and version control * Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization), either PhD or Advanced MS degree.
Machine Learning Engineer - Physical AI
San Diego, CA · On-site
$120K/yr
Apply Bayesian optimization, surrogate modeling, Gaussian processes, and DoE for high-dimensional process parameter optimization * Analyze 3D metrology and inspection data, define quality metrics ...
Quick apply
Machine Learning Engineer - Physical AI
San Diego, CA · On-site
$120K/yr
Apply Bayesian optimization, surrogate modeling, Gaussian processes, and DoE for high-dimensional process parameter optimization * Analyze 3D metrology and inspection data, define quality metrics ...
Experience with Bayesian networks or probabilistic modeling. * Experience with uncertainty quantification techniques, such as Bayesian Inference, Monte Carlo simulation. * Experience with building ...
Experience with Bayesian networks or probabilistic modeling. * Experience with uncertainty quantification techniques, such as Bayesian Inference, Monte Carlo simulation. * Experience with building ...
Data Scientist
San Francisco, CA · On-site +1
$160K - $200K/yr
... with model deployment, monitoring and version control * Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization), either PhD or Advanced MS degree.
Data Scientist
San Francisco, CA · On-site +1
$160K - $200K/yr
... with model deployment, monitoring and version control * Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization), either PhD or Advanced MS degree.
... models, Bayesian deep learning, equivariant CNNs, Bayesian optimizations, reinforcement learning, unsupervised learning, and graph NNs). • Drives systems innovations for model efficiency ...
... models, Bayesian deep learning, equivariant CNNs, Bayesian optimizations, reinforcement learning, unsupervised learning, and graph NNs). • Drives systems innovations for model efficiency ...
Tech Lead Manager, Foundation Models
Mountain View, CA · On-site
$298K - $368K/yr
AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust ...
Tech Lead Manager, Foundation Models
Mountain View, CA · On-site
$298K - $368K/yr
AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust ...
Bayesian Modeling information
What is the difference between Bayesian Modeling vs Data Scientist?
| Aspect | Bayesian Modeling | Data Scientist |
|---|---|---|
| Required Credentials | Statistics, Mathematics, Data Analysis | Statistics, Computer Science, Data Analysis |
| Work Environment | Research-focused, statistical modeling | Cross-functional, data analysis, visualization |
| Industry Usage | Research, academia, specialized analytics | Business, tech, finance, healthcare |
| Common Search/Comparison | Yes | Yes |
Bayesian Modeling and Data Scientists often overlap in skills like statistics and data analysis. Bayesian Modeling specializes in probabilistic models and statistical inference, while Data Scientists have broader roles including data cleaning, visualization, and machine learning. Both roles are essential in data-driven industries, but Bayesian Modeling is more focused on advanced statistical techniques.
What are the key skills and qualifications needed to thrive as a Bayesian Modeler, and why are they important?
To thrive as a Bayesian Modeler, you need a solid background in statistics, probability theory, and mathematical modeling, often supported by an advanced degree in statistics, mathematics, or a related field. Proficiency with programming languages such as R, Python, or Stan, and experience with statistical software and Bayesian inference tools are essential. Strong analytical thinking, attention to detail, and effective communication skills help in interpreting results and collaborating with multidisciplinary teams. These skills ensure accurate model development, reliable data-driven insights, and clear communication of complex findings to stakeholders.
How does a Bayesian Modeling specialist typically collaborate with cross-functional teams in a workplace setting?
Bayesian Modeling specialists often work closely with data scientists, software engineers, and domain experts to integrate probabilistic models into larger analytical or production systems. They are involved in translating complex statistical concepts into actionable insights and recommendations tailored to business needs. Effective communication is key, as they must present findings to both technical and non-technical stakeholders, ensuring that model assumptions and results are clearly understood. Collaboration may also include contributing to code reviews, sharing best practices for model validation, and mentoring colleagues on Bayesian methodologies.
What is Bayesian modeling?
Bayesian modeling is a statistical approach that uses Bayes' Theorem to update the probability of a hypothesis as more data becomes available. It incorporates prior beliefs or knowledge, combines them with observed data, and produces a posterior probability distribution to guide inference and decision-making. This approach is widely used in various fields such as machine learning, data science, and scientific research for tasks like parameter estimation, prediction, and model selection.
What are popular job titles related to Bayesian Modeling jobs in California? For Bayesian Modeling jobs in California, the most frequently searched job titles are:
- Internship Applied Intelligence
- Intern Data Scientist Apprentice
- Graph Anomaly Detection
- Data Scientist Internship
- Internship Bioinformatics Data Scientist
- Manager Scientific Database Curator
- Internship Marine Biologist
- Overnight Computational Linguistics Intern
- Internship Junior Data Scientist
- Data Scientist R Remote
What job categories do people searching Bayesian Modeling jobs in California look for? The top searched job categories for Bayesian Modeling jobs in California are:
Meta rating
7.5
Based on 44 frontline employees who took The Breakroom Quiz
130th of 202 rated software companies
Job description
As a Senior Analyst in Meta’s Competitive Intelligence organization, you will operate at the intersection of advanced analytics, data science, and market strategy. You will lead major projects and product areas—often in environments of significant ambiguity or technical complexity—driving both technical and business outcomes. This is a hands-on, high-impact role for builders who thrive on solving real problems. This role demands a unique blend of analytical and statistical expertise, strategic thinking , and the ability to translate complex insights into impactful product and business decisions. You will be recognized as a thought partner by cross-functional leads and will help shape the analytical foundations that inform how we build and grow our products.
Competitive Intelligence Research Responsibilities:
Minimum Qualifications:
Preferred Qualifications:
About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Competitive Intelligence Research Responsibilities:
- Market Strategy: Influence organization-level product direction through data-driven narratives and an in depth understanding of the market landscape. Demonstrated experience operating at scale, and across ambiguous, environments with working knowledge of econometrics. As a quantitative market-strategist, you will blend practical and applied understanding with technical expertise, including pressure-testing data for quality, reliability, understanding data-biases and being solution driven
- Analytics Leadership: Conduct advanced analyses with 3P datasets, develop statistical models and forecasts, and deliver actionable insights that informs market and business strategy. These include, but are not limited to:
- Data onboarding: Identify, onboard, and rigorously evaluate 3P datasets to determine their signal-to-noise ratio and predictive power
- Data triangulation: Triangulate data from many sources of imperfect information. Synthesize multiple, low-fidelity 3rd-party signals into a single high-fidelity trend report using Bayesian aggregation or other methods
- Data transformation: Apply quasi-experimental designs (e.g., synthetic control, diff-in-diff) to isolate the impact of exogenous market shocks and competitor actions on internal performance metrics, using 3rd-party behavioral and economic datasets
- Insight and implications: Apply guidance from such analyses to increase the accuracy of forecasts and better understand market trends
- Technical & Methodological Expertise: Act as a recognized professional in a technical or methodological area (e.g., causal inference, bayesian aggregation), driving the adoption of advanced methods and organization-wide best practices that raise the bar for the entire team
- Data Governance & Quality: Ensure data privacy, security, and compliance with organizational standards. Champion data quality frameworks and documentation practices that enable credible reproducible analyses
- Resourceful, adaptable professional with a bias for action
Minimum Qualifications:
- Bachelors degree and a minimum of 6 years of work experience (minimum of 4 years with a Ph.D.) in business intelligence, product analytics, or economic or strategy consulting in a technology environment with increasing scope and impact
- Demonstrated skill to ethically source, validate, and synthesize high-signal insights from people (e.g., stakeholder interviews, skilled conversations, field research, and relationship-based information gathering) while maintaining high standards for privacy, consent, and integrity
- Proficiency in AI-powered tools: Demonstrate working knowledge of Generative AI technologies (e.g., LLM and AI agents) and experience designing, prompting, and orchestrating AI systems (e.g., prompt engineering) to automate data analyses, synthesize insights, and execute multi-step analytical tasks (e.g., prompting agent to clean datasets, build visualizations)
- Practical working understanding of data-analytics tools, and direct experience managing, analyzing, manipulating and interpreting 1P and external 3P datasets
- Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R)
- Proven experience with statistical analysis including causal inference (e.g., randomized control trials, quasi-experimentation such as synthetic control, diff-in-diff, meta-analyses), and/or bayesian aggregation (e.g., bayesian pooling, hierarchical modeling)
- Demonstrated communication skills and experience presenting complex findings to both technical and non-technical stakeholders
- Demonstrated experience thriving in ambiguous environments and shape new analytics organizations or products
Preferred Qualifications:
- Master's or Ph.D. Degree in a quantitative field such as Quantitative Economics or Political Science, Operations Research, Data Science, Computer Science, Physics, Business, or Mathematics
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$177,000/year to $247,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$177,000/year to $247,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
About Meta
Sourced by ZipRecruiter
Industry
Internet and it, media and telecom and software development
Company size
10,000+ Employees
Headquarters location
Menlo Park, CA, US