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Bayesian Jobs Near Me

Strong understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling * Financial Services ...

... as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling Financial Services background Exempt Status: (Yes = not eligible for overtime pay ...

Strong understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling * Financial Services ...

Understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling * Experience with Cloud Machine ...

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How much do bayesian jobs pay per year?

As of Jun 30, 2026, the average yearly pay for bayesian in the United States is $159,999.00, according to ZipRecruiter salary data. Most workers in this role earn between $155,000.00 and $165,000.00 per year, depending on experience, location, and employer.
What cities are hiring for Bayesian jobs? Cities with the most Bayesian job openings:
What states have the most Bayesian jobs? States with the most job openings for Bayesian jobs include:
What are the most commonly searched types of Bayesian jobs? The most popular types of Bayesian jobs are:
A map of the United States highlighting the number of Bayesian job openings by state according to ZipRecruiter. The image is accompanied by a detailed chart listing the number of Bayesian job openings in each state, with California having the most at 2 and Hawaii the least at 0.
Applied ML Scientist - Active Learning

Applied ML Scientist - Active Learning

Hexion Inc.

Columbus, OH • On-site

Full-time

Posted 5 days ago


Job description

Job Summary:
Hexion Inc. is a company that pushes boundaries and creates impactful solutions through science. They are seeking an Applied ML Scientist to lead optimization and active-learning campaigns, collaborating with R&D and manufacturing to enhance processes and drive innovation.
Responsibilities:
• Lead the design and execution of optimization and active-learning campaigns across chemistry, formulation, and process development.
• Collaborate with R&D and manufacturing on framing optimization problems with design spaces, decision variables, objectives, and hard and soft constraints.
• Design and coordinate sequential experiment campaigns using Bayesian optimization and active learning, accounting for operational variabilities and constraints.
• Select and maintain surrogate models for acquisition, using model uncertainty to drive the search and respecting each model's domain of validity.
• Drive closed-loop optimization that connects surrogate models to experimentation, with emphasis on decision quality, exploration versus exploitation, and actionable recommendations.
• Partner with ML engineers, software engineers, and process engineers to deploy and monitor optimization systems.
• Explore and adopt emerging ML methods, including LLM and agentic approaches, to advance optimization.
• Communicate methods, results, and their limitations clearly to technical and non-technical audiences.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Data Science, Statistics, Operations Research, or a related field, with substantial relevant experience in ML modeling or optimization experience for chemistry, formulation, process, or manufacturing problems.
• 7+ years experience.
• Demonstrated expertise in Bayesian optimization and Gaussian processes, including kernels, acquisition functions, and batch, multi-objective, and constrained settings.
• Experience designing and running experiment campaigns or closed-loop optimization.
• Experience in applied statistics and uncertainty quantification, with emphasis on calibrated posteriors that drive acquisition.
• Strong Python skills and experience with mainstream Python-based ML and Bayesian optimization frameworks and tools.
• Active use of AI-assisted coding and other AI tools in daily work, with familiarity with emerging ML methods including LLM and agentic approaches.
• Strong communication, collaboration, and stakeholder management skills for working with R&D, manufacturing, and business teams.
Preferred:
• Master's degree in Computer Science, Data Science, Statistics, Operations Research, or a related field.
• Experience with active learning and physics-informed approaches for optimization in chemical synthesis, formulation, or process development.
• Experience working with manufacturing, process, quality, or plant data, including issues such as batch-to-batch variability, raw-material variability, model drift, and changing operating conditions.
• Familiar with ML engineering core tasks and techniques, such as data and optimization pipelines, model deployment, and MLOps.
• Knowledge of chemistry ML core areas such as cheminformatics, molecular representation, predictive modeling, and chemistry foundation models.
Company:
Based in Columbus, Ohio, Hexion Inc. is a leading global producer of adhesives and performance materials. Founded in , the company is headquartered in Columbus, USA, with a team of 1001-5000 employees. The company is currently Late Stage.