San Francisco, CA · On-site
$200K - $270K/yr
About the role: We're hiring a Senior / Principal ML Scientist to design and scale Bayesian optimization and reinforcement-learning frameworks that guide molecular engineering campaigns through ...
San Francisco, CA · On-site
$200K - $270K/yr
About the role: We're hiring a Senior / Principal ML Scientist to design and scale Bayesian optimization and reinforcement-learning frameworks that guide molecular engineering campaigns through ...
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 ...
$200K - $300K/yr
Portfolio of AI-enabled discovery programs spanning co-scientist agents, Bayesian optimization, and sequential learning - deployed across global R&D and expanding to new material systems * Leadership ...
$200K - $300K/yr
Portfolio of AI-enabled discovery programs spanning co-scientist agents, Bayesian optimization, and sequential learning - deployed across global R&D and expanding to new material systems * Leadership ...
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 ...
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 ...
San Jose, CA · On-site
$200K - $300K/yr
Portfolio of AI-enabled discovery programs spanning co-scientist agents, Bayesian optimization, and sequential learning - deployed across global R&D and expanding to new material systems * Leadership ...
San Jose, CA · On-site
$200K - $300K/yr
Portfolio of AI-enabled discovery programs spanning co-scientist agents, Bayesian optimization, and sequential learning - deployed across global R&D and expanding to new material systems * Leadership ...
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 ...
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 ...
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 ...
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 ...
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 ...
San Mateo, CA · On-site +1
$175K - $248K/yr
... Bayesian experimentation; designing multi-dimensional test structures and interpreting results across user segments; mitigating validity threats including SRM, contamination, and multi-exposure ...
San Mateo, CA · On-site +1
$175K - $248K/yr
... Bayesian experimentation; designing multi-dimensional test structures and interpreting results across user segments; mitigating validity threats including SRM, contamination, and multi-exposure ...
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 ...
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 ...
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 ...
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 ...
$205K - $278K/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 ...
$205K - $278K/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 ...
Mountain View, CA · On-site
$205K - $278K/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 ...
Mountain View, CA · On-site
$205K - $278K/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 ...
Mountain View, CA · On-site
$205K - $278K/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 ...
Mountain View, CA · On-site
$205K - $278K/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 ...
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 ...
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 ...
Mountain View, CA · On-site
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 ...
Mountain View, CA · On-site
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 ...
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 ...
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 ...
$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
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.
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.
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.
$200K - $270K/yr
Full-time
Posted 5 days ago
Design and scale Bayesian optimization and reinforcement-learning frameworks to guide molecular engineering campaigns through iterative design-build-test-learn cycles.
Build scientific and engineering scaffolding for active-learning and closed-loop optimization, including data ingestion, ML modeling, and library design.
Collaborate with wet-lab scientists to define optimization objectives and encode domain-specific priors and constraints.
