Recent examples of our work include a Bayesian experimentation engine that powers Product Page Optimization in App Store Analytics, and differential privacy solutions behind the Peer-Group Benchmarks ...
Recent examples of our work include a Bayesian experimentation engine that powers Product Page Optimization in App Store Analytics, and differential privacy solutions behind the Peer-Group Benchmarks ...
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 ...
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 ...
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 ...
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 ...
Senior ML Engineer
San Francisco, CA · On-site
$123K - $169K/yr
Responsibilities : • Training machine learning models over billions of data points. • Quantifying predictive uncertainty using probabilistic and Bayesian methods. • Creating models that quickly ...
Senior ML Engineer
San Francisco, CA · On-site
$123K - $169K/yr
Responsibilities : • Training machine learning models over billions of data points. • Quantifying predictive uncertainty using probabilistic and Bayesian methods. • Creating models that quickly ...
Senior Machine Learning Engineer, Developer Product Analytics
Cupertino, CA · On-site
$184K - $277K/yr
Recent examples of our work include a Bayesian experimentation engine that powers Product Page Optimization in App Store Analytics, and differential privacy solutions behind the Peer-Group Benchmarks ...
Senior Machine Learning Engineer, Developer Product Analytics
Cupertino, CA · On-site
$184K - $277K/yr
Recent examples of our work include a Bayesian experimentation engine that powers Product Page Optimization in App Store Analytics, and differential privacy solutions behind the Peer-Group Benchmarks ...
... Bayesian optimization workflows to analyze existing, and design new, small and large molecules. • You will be expected to form close working relationships with small molecule and protein ...
... Bayesian optimization workflows to analyze existing, and design new, small and large molecules. • You will be expected to form close working relationships with small molecule and protein ...
Competitive Intelligence Lead
San Francisco, CA · On-site
$177K/yr
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 ...
Competitive Intelligence Lead
San Francisco, CA · On-site
$177K/yr
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 ...
Principal AI Scientist - AI Foundation
$273K - $369K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Principal AI Scientist - AI Foundation
$273K - $369K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Staff AI Scientist
Mountain View, CA · On-site
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Staff AI Scientist
Mountain View, CA · On-site
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Principal AI Scientist - AI Foundation
Mountain View, CA · On-site
$273K - $369K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Principal AI Scientist - AI Foundation
Mountain View, CA · On-site
$273K - $369K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Proficient in Bayesian estimation concepts and Kalman filtering Proficient in statistics concepts and statistical data analysis Proficient in C++ Familiar with modern object-oriented programming ...
Proficient in Bayesian estimation concepts and Kalman filtering Proficient in statistics concepts and statistical data analysis Proficient in C++ Familiar with modern object-oriented programming ...
Staff AI Scientist
Mountain View, CA · On-site
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Staff AI Scientist
Mountain View, CA · On-site
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Staff AI Scientist
Mountain View, CA · On-site
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Staff AI Scientist
Mountain View, CA · On-site
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Principal AI Scientist - AI Foundation
Mountain View, CA · On-site
$273K - $369K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Principal AI Scientist - AI Foundation
Mountain View, CA · On-site
$273K - $369K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Staff AI Scientist
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Staff AI Scientist
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Staff AI Scientist
Mountain View, CA · On-site
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Staff AI Scientist
Mountain View, CA · On-site
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Staff AI Scientist
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Staff AI Scientist
$209K - $283K/yr
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and ...
Applied Data Scientist
Santa Rosa, CA · On-site
$117K - $196K/yr
Familiarity with Bayesian Optimization and feature engineering for time-series or signal data . * Ability to move fluidly between data exploration, engineering, and modeling tasks. Desired ...
Applied Data Scientist
Santa Rosa, CA · On-site
$117K - $196K/yr
Familiarity with Bayesian Optimization and feature engineering for time-series or signal data . * Ability to move fluidly between data exploration, engineering, and modeling tasks. Desired ...
Data Scientist
Los Angeles, CA · On-site
$170K - $300K/yr
Bayesian and hierarchical modeling for small data; physics-informed ML * Survival and reliability modeling (tool life, degradation) * Aerospace or precision-manufacturing background; DFM intuition
Data Scientist
Los Angeles, CA · On-site
$170K - $300K/yr
Bayesian and hierarchical modeling for small data; physics-informed ML * Survival and reliability modeling (tool life, degradation) * Aerospace or precision-manufacturing background; DFM intuition
Data Scientist
Torrance, CA · On-site
$170K - $300K/yr
Bayesian and hierarchical modeling for small data; physics-informed ML * Survival and reliability modeling (tool life, degradation) * Aerospace or precision-manufacturing background; DFM intuition
Quick apply
Data Scientist
Torrance, CA · On-site
$170K - $300K/yr
Bayesian and hierarchical modeling for small data; physics-informed ML * Survival and reliability modeling (tool life, degradation) * Aerospace or precision-manufacturing background; DFM intuition
Bayesian information
See California salary details
$146.4K - $148.4K
7% of jobs
$148.4K - $150.3K
10% of jobs
$152K is the 25th percentile. Wages below this are outliers.
$150.3K - $152.3K
10% of jobs
$152.3K - $154.2K
10% of jobs
$154.2K - $156.2K
10% of jobs
The median wage is $156.9K / yr.
$156.2K - $158.1K
10% of jobs
$158.1K - $160.1K
10% of jobs
$161.9K is the 75th percentile. Wages above this are outliers.
$160.1K - $162.1K
10% of jobs
$162.1K - $164K
10% of jobs
$164K - $166K
10% of jobs
$166K - $167.9K
4% of jobs
$146.4K
$156.7K
$167.9K
How much do bayesian jobs pay per year?
As of Sep 2, 2026, the average yearly pay for bayesian in California is $156,676.00, according to ZipRecruiter salary data. Most workers in this role earn between $151,780.00 and $161,572.00 per year, depending on experience, location, and employer.
What is a Bayesian?
A Bayesian job typically involves applying Bayesian statistics, probabilistic modeling, and inference techniques to analyze data and make decisions under uncertainty. Professionals in this field use Bayes' theorem to update beliefs based on new evidence, often working in areas like machine learning, finance, healthcare, and research. Common roles include Bayesian statisticians, data scientists, and researchers who build probabilistic models to improve predictions and decision-making.
What are the typical projects or challenges faced in a Bayesian role?
In a Bayesian role, you’ll often work on projects involving probabilistic modeling, uncertainty quantification, and predictive analytics for real-world decision-making. Common challenges include structuring prior distributions, ensuring computational efficiency for complex models, and clearly explaining Bayesian results to non-technical stakeholders. You might collaborate closely with data engineers, domain experts, and business analysts to refine models and translate findings into actionable recommendations. This role offers the opportunity to tackle diverse analytical problems across industries like healthcare, finance, or tech, supporting ongoing professional growth and learning.
What are the key skills and qualifications needed to thrive in a Bayesian role, and why are they important?
To thrive as a Bayesian (typically a Bayesian Data Scientist or Statistician), you need a strong background in probability theory, statistical modeling, and mathematics, often with an advanced degree in statistics, data science, or a related quantitative field. Experience with programming languages such as Python or R, Bayesian analysis libraries (e.g., Stan, PyMC), and familiarity with statistical software are commonly required. Analytical thinking, collaborative teamwork, and the ability to communicate complex results clearly are valuable soft skills in this role. These abilities are essential for designing robust models, interpreting data accurately, and delivering actionable insights to interdisciplinary teams.
What are the most commonly searched types of Bayesian jobs in California?
The most popular types of Bayesian jobs in California are:
What are popular job titles related to Bayesian jobs in California?
For Bayesian jobs in California, the most frequently searched job titles are:
What job categories do people searching Bayesian jobs in California look for?
The top searched job categories for Bayesian jobs in California are:
What cities in California are hiring for Bayesian jobs?
Cities in California with the most Bayesian job openings:
Full-time
Re-posted 8 days ago
Apple rating
8.1
Based on 680 frontline employees who took The Breakroom Quiz
6th of 30 rated technology retailers
Job description
Apple Services Engineering powers the digital storefronts and partner platforms that millions rely on every day, from the App Store, Apple Music, and Podcasts to the analytics platforms that serve the developers and artists who create for them (App Store Analytics, Apple Music for Artists, Podcast Analytics). The Product Data Science team builds the statistical, ML, and AI-powered algorithms behind these platforms, focused on content-partner analytics tools, experimentation engines, privacy-preserving analytics, and charting systems used by millions of businesses and users worldwide. We are looking for a scientist who has shipped end-to-end ML solutions in production, is driven to find the next high-impact problem, and wants to do it at Apple scale.
Description
Product Data Science sits within Apple Services Engineering, the org that runs Apple's content platforms end-to-end. The team builds the intelligence layer behind partner-facing analytics applications and Apple's global content charts. Recent examples of our work include a Bayesian experimentation engine that powers Product Page Optimization in App Store Analytics, and differential privacy solutions behind the Peer-Group Benchmarks feature, giving developers privacy-safe performance insights they could not get anywhere else. We stay close to the research and encourage the team to do the same, whether in Bayesian methods, privacy-preserving ML, or applied AI. There are regular opportunities to present work at internal tech talks and external conferences. We care deeply about translating research into features that give content partners materially useful insights, and help users discover more of what Apple's platforms have to offer.
Minimum Qualifications
First-principles understanding of the methods you use: able to explain why an algorithm works, its assumptions, and where it breaks.
Proficiency across multiple ML domains: supervised and unsupervised learning, deep learning, time-series modeling, and Bayesian statistics.
Production-quality software engineering in Python, including reusable service design and the full deployment lifecycle.
Experience taking 0-to-1 features end-to-end: problem framing, algorithm design, and production deployment.
MS or PhD in Statistics, Computer Science, Machine Learning, or a related quantitative field. Candidates with equivalent industry experience will be considered.
Preferred Qualifications
3-5+ years of industry experience designing and deploying ML or statistical solutions in production.
Experience with differential privacy, causal inference, or statistical experimentation (A/B testing, Bayesian experimentation).
Familiarity with distributed data platforms and web-scale pipelines.
Exposure to applied AI, LLMs, and agentic systems.
Production engineering experience in Scala or Spark.
You think in user outcomes, not model metrics.
Communicates clearly across technical and non-technical audiences, and across time zones.
Comfortable working independently and collaboratively in a geographically distributed, cross-functional org.
Description
Product Data Science sits within Apple Services Engineering, the org that runs Apple's content platforms end-to-end. The team builds the intelligence layer behind partner-facing analytics applications and Apple's global content charts. Recent examples of our work include a Bayesian experimentation engine that powers Product Page Optimization in App Store Analytics, and differential privacy solutions behind the Peer-Group Benchmarks feature, giving developers privacy-safe performance insights they could not get anywhere else. We stay close to the research and encourage the team to do the same, whether in Bayesian methods, privacy-preserving ML, or applied AI. There are regular opportunities to present work at internal tech talks and external conferences. We care deeply about translating research into features that give content partners materially useful insights, and help users discover more of what Apple's platforms have to offer.
Minimum Qualifications
First-principles understanding of the methods you use: able to explain why an algorithm works, its assumptions, and where it breaks.
Proficiency across multiple ML domains: supervised and unsupervised learning, deep learning, time-series modeling, and Bayesian statistics.
Production-quality software engineering in Python, including reusable service design and the full deployment lifecycle.
Experience taking 0-to-1 features end-to-end: problem framing, algorithm design, and production deployment.
MS or PhD in Statistics, Computer Science, Machine Learning, or a related quantitative field. Candidates with equivalent industry experience will be considered.
Preferred Qualifications
3-5+ years of industry experience designing and deploying ML or statistical solutions in production.
Experience with differential privacy, causal inference, or statistical experimentation (A/B testing, Bayesian experimentation).
Familiarity with distributed data platforms and web-scale pipelines.
Exposure to applied AI, LLMs, and agentic systems.
Production engineering experience in Scala or Spark.
You think in user outcomes, not model metrics.
Communicates clearly across technical and non-technical audiences, and across time zones.
Comfortable working independently and collaboratively in a geographically distributed, cross-functional org.
About Apple
Sourced by ZipRecruiter
Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.
Industry
Computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Cupertino, CA, US
Year founded
1976