Surrogate Modeling & Automated Design Space Exploration (DSE): Build physics informed ML surrogates ... DSE (e.g., Bayesian Optimization, NSGA II) to target objectives (efficiency/BSFC, mass, cost ...
Surrogate Modeling & Automated Design Space Exploration (DSE): Build physics informed ML surrogates ... DSE (e.g., Bayesian Optimization, NSGA II) to target objectives (efficiency/BSFC, mass, cost ...
Statistics Graduate Level Tutor
Detroit, MI · Remote
$40/hr
... Bayesian inference, regression analysis, multivariate methods, experimental design, and ... Ability to explain asymptotic theory, Neyman-Pearson lemma, and generalized linear models while ...
Statistics Graduate Level Tutor
Detroit, MI · Remote
$40/hr
... Bayesian inference, regression analysis, multivariate methods, experimental design, and ... Ability to explain asymptotic theory, Neyman-Pearson lemma, and generalized linear models while ...
Senior Machine Learning Engineer (GenAI, LLM, GCP) Only W2//Dearborn, MI
Dearborn, MI · On-site
$96K - $131K/yr
... modeling techniques such as decision trees, logistic regression, Bayesian analysis, and deep learning methods, alongside prompt engineering, retrieval-augmented generation (RAG), and parameter ...
Quick apply
Senior Machine Learning Engineer (GenAI, LLM, GCP) Only W2//Dearborn, MI
Dearborn, MI · On-site
$96K - $131K/yr
... modeling techniques such as decision trees, logistic regression, Bayesian analysis, and deep learning methods, alongside prompt engineering, retrieval-augmented generation (RAG), and parameter ...
Autonomous Driving Vehicle Perception Engineer
Northville, MI · On-site
$80K - $100K/yr
Develop, test, and deploy machine learning models for perception tasks such as object detection and ... Bayesian filtering, and data association. * Hands-on experience with intrinsic and extrinsic ...
Quick apply
Autonomous Driving Vehicle Perception Engineer
Northville, MI · On-site
$80K - $100K/yr
Develop, test, and deploy machine learning models for perception tasks such as object detection and ... Bayesian filtering, and data association. * Hands-on experience with intrinsic and extrinsic ...
Senior Data Scientist
Birmingham, MI · On-site
... Bayesian Inference, Markov Chain Monte-Carlo (MCMC) * Familiarity with common advanced marketing analytics solutions such as Customer Segmentation, Marketing Mix Modeling (MMM), Multi-touch ...
Senior Data Scientist
Birmingham, MI · On-site
... Bayesian Inference, Markov Chain Monte-Carlo (MCMC) * Familiarity with common advanced marketing analytics solutions such as Customer Segmentation, Marketing Mix Modeling (MMM), Multi-touch ...
Senior Data Scientist
Birmingham, MI · On-site
... Bayesian Inference, Markov Chain Monte-Carlo (MCMC) * Familiarity with common advanced marketing analytics solutions such as Customer Segmentation, Marketing Mix Modeling (MMM), Multi-touch ...
Senior Data Scientist
Birmingham, MI · On-site
... Bayesian Inference, Markov Chain Monte-Carlo (MCMC) * Familiarity with common advanced marketing analytics solutions such as Customer Segmentation, Marketing Mix Modeling (MMM), Multi-touch ...
Foundational knowledge of probabilistic robotics and related methods (State Space Modeling, Kalman filtering, or Bayesian approaches) * Interest in convex optimization, optimal control, or model ...
Foundational knowledge of probabilistic robotics and related methods (State Space Modeling, Kalman filtering, or Bayesian approaches) * Interest in convex optimization, optimal control, or model ...
Foundational knowledge of probabilistic robotics and related methods (State Space Modeling, Kalman filtering, or Bayesian approaches) * Interest in convex optimization, optimal control, or model ...
Foundational knowledge of probabilistic robotics and related methods (State Space Modeling, Kalman filtering, or Bayesian approaches) * Interest in convex optimization, optimal control, or model ...
Bayesian Modeling information
See Troy, MI salary details
$9.80 - $16.07
4% of jobs
$16.07 - $22.35
1% of jobs
$22.35 - $28.62
2% of jobs
$28.62 - $34.90
0% of jobs
$34.90 - $41.18
3% of jobs
$41.18 - $47.45
8% of jobs
$49.71 is the 25th percentile. Wages below this are outliers.
$47.45 - $53.73
17% of jobs
The median wage is $57.41 / hr.
$53.73 - $60
24% of jobs
$64.07 is the 75th percentile. Wages above this are outliers.
$60 - $66.28
23% of jobs
$66.28 - $72.55
12% of jobs
$72.55 - $78.83
5% of jobs
$9
$55
$78
How much do bayesian modeling jobs pay per hour?
As of Sep 13, 2026, the average hourly pay for bayesian modeling in Troy, MI is $55.65, according to ZipRecruiter salary data. Most workers in this role earn between $49.90 and $64.71 per hour, depending on experience, location, and employer.
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.
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 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.
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 popular job titles related to Bayesian Modeling jobs in Troy, MI?
For Bayesian Modeling jobs in Troy, MI, the most frequently searched job titles are:
What job categories do people searching Bayesian Modeling jobs in Troy, MI look for?
The top searched job categories for Bayesian Modeling jobs in Troy, MI are:
What cities near Troy, MI are hiring for Bayesian Modeling jobs?
Cities near Troy, MI with the most Bayesian Modeling job openings:
Automotive Propulsion Software Research Engineer
Warren, MI • On-site
Lorven Technologies
• IT Services • 51 - 200 employees51 - 200 employees
Full-time
Re-posted 14 days ago
Job description
Role: Automotive Propulsion Software Research Engineer
Location: Fully onsite. Warren, MI
Contract role
Job description:
Develop an LLM and agent based assistant to automate simulation setup, run deck generation, boundary condition/mesh recommendations, results review, and requirements alignment across 1D/3D tools (e.g., GT POWER/Simcenter Amesim, ANSYS/STAR CCM+, MATLAB/Simulink).
Surrogate Modeling & Automated Design Space Exploration (DSE): Build physics informed ML surrogates for key propulsion performance metrics (e.g., torque, BSFC/efficiency, thermal limits, emissions proxies, e drive efficiency maps) and integrate them with active learning data generation and multi objective optimization
MS or PHD in Computer Science, Computer Engineering, or Electrical Engineering
Skillset: Python programming (critical); Experience in AI/ML, preferably Generative AI (critical); familiarity with embedded software development lifecycle and systems engineering activities
• System architecture covering data sources (requirements, prior studies, PLM), tools (1D/3D solvers), and results storage (Lakehouse).
• Document parsing pipelines for requirements/specs/test plans; establish content normalization (Markdown/JSON).
• Agent workflows for: interpreting change requests, proposing simulation plans, generating run decks/templates, mesh/BC suggestions, and automated post processing.
• Chat + form based UI to request studies, generate inputs, and review outputs.
• Integration with Databricks (Lakehouse, MLflow, Model Serving) for versioning, observability, and scalable compute.
• Define target responses (e.g., torque map, efficiency map, pressure ratios, temperatures, emissions proxies), inputs (geometry/controls/operating points), and constraints.
• Data model and schema for simulation inputs/outputs; provenance and UQ metadata.
• Orchestrate solver sweeps (1D/CFD/FEA where applicable) to seed the dataset.
• Implement adaptive sampling/active learning to target high value points that reduce model error.
• Train candidate surrogates (e.g., GPR, XGBoost/TabNet, feedforward NNs, physics informed NNs).
• Cross validation, error budgets, calibration; uncertainty quantification and guardbanding.
• Integrate surrogates with DSE (e.g., Bayesian Optimization, NSGA II) to target objectives (efficiency/BSFC, mass, cost, thermal margins) under constraints (emissions/temperature/packaging).
• Optional coupling to MDAO toolchains (e.g., ModelCenter/HEEDS/Simcenter).
Location: Fully onsite. Warren, MI
Contract role
Job description:
Develop an LLM and agent based assistant to automate simulation setup, run deck generation, boundary condition/mesh recommendations, results review, and requirements alignment across 1D/3D tools (e.g., GT POWER/Simcenter Amesim, ANSYS/STAR CCM+, MATLAB/Simulink).
Surrogate Modeling & Automated Design Space Exploration (DSE): Build physics informed ML surrogates for key propulsion performance metrics (e.g., torque, BSFC/efficiency, thermal limits, emissions proxies, e drive efficiency maps) and integrate them with active learning data generation and multi objective optimization
MS or PHD in Computer Science, Computer Engineering, or Electrical Engineering
Skillset: Python programming (critical); Experience in AI/ML, preferably Generative AI (critical); familiarity with embedded software development lifecycle and systems engineering activities
• System architecture covering data sources (requirements, prior studies, PLM), tools (1D/3D solvers), and results storage (Lakehouse).
• Document parsing pipelines for requirements/specs/test plans; establish content normalization (Markdown/JSON).
• Agent workflows for: interpreting change requests, proposing simulation plans, generating run decks/templates, mesh/BC suggestions, and automated post processing.
• Chat + form based UI to request studies, generate inputs, and review outputs.
• Integration with Databricks (Lakehouse, MLflow, Model Serving) for versioning, observability, and scalable compute.
• Define target responses (e.g., torque map, efficiency map, pressure ratios, temperatures, emissions proxies), inputs (geometry/controls/operating points), and constraints.
• Data model and schema for simulation inputs/outputs; provenance and UQ metadata.
• Orchestrate solver sweeps (1D/CFD/FEA where applicable) to seed the dataset.
• Implement adaptive sampling/active learning to target high value points that reduce model error.
• Train candidate surrogates (e.g., GPR, XGBoost/TabNet, feedforward NNs, physics informed NNs).
• Cross validation, error budgets, calibration; uncertainty quantification and guardbanding.
• Integrate surrogates with DSE (e.g., Bayesian Optimization, NSGA II) to target objectives (efficiency/BSFC, mass, cost, thermal margins) under constraints (emissions/temperature/packaging).
• Optional coupling to MDAO toolchains (e.g., ModelCenter/HEEDS/Simcenter).
About Lorven technologies
Sourced by ZipRecruiter
Lorven Technologies, headquartered in Plainsboro, New Jersey, United States, is a reputable company in the technology industry, specializing in providing effective IT solutions and consulting services. The company's official website, lorventech.com, offers comprehensive insights into its offerings which include but are not limited to software development, IT consulting, project management, and business analysis. Since its inception, Lorven Technologies has been committed to ensuring efficiency and reliability in delivering IT services to its global clientele, establishing itself as a trusted name in the industry.
Industry
It services
Company size
51 - 200 Employees
Headquarters location
Plainsboro, NJ, US
Year founded
2001