... Bayesian optimization and active learning, accounting for operational variabilities and constraints. • Select and maintain surrogate models for acquisition, using model uncertainty to drive the ...
... Bayesian optimization and active learning, accounting for operational variabilities and constraints. • Select and maintain surrogate models for acquisition, using model uncertainty to drive the ...
Develop and apply RL techniques, including Contextual Bandits, Q-learning, SARSA, and concepts like Thompson Sampling and Bayesian Optimization, to solve pricing and optimization challenges. • AI ...
Develop and apply RL techniques, including Contextual Bandits, Q-learning, SARSA, and concepts like Thompson Sampling and Bayesian Optimization, to solve pricing and optimization challenges. • AI ...
... 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 ...
Senior Machine Learning Scientist I, Model-Driven Optimization
Somerville, MA · On-site
$170 - $210/hr
The ideal candidate combines depth in probabilistic machine learning, Bayesian optimization, active learning, or related approaches with the practical judgment and engineering discipline to turn ...
Senior Machine Learning Scientist I, Model-Driven Optimization
Somerville, MA · On-site
$170 - $210/hr
The ideal candidate combines depth in probabilistic machine learning, Bayesian optimization, active learning, or related approaches with the practical judgment and engineering discipline to turn ...
Senior Machine Learning Scientist I/II, Model-Driven Optimization
Somerville, MA · On-site
$99K - $136K/yr
The ideal candidate combines depth in probabilistic machine learning, Bayesian optimization, active learning, or related approaches with the practical judgment and engineering discipline to turn ...
Senior Machine Learning Scientist I/II, Model-Driven Optimization
Somerville, MA · On-site
$99K - $136K/yr
The ideal candidate combines depth in probabilistic machine learning, Bayesian optimization, active learning, or related approaches with the practical judgment and engineering discipline to turn ...
Senior Machine Learning Scientist I/II, Model-Driven Optimization
Somerville, MA · On-site
$99K - $136K/yr
The ideal candidate combines depth in probabilistic machine learning, Bayesian optimization, active learning, or related approaches with the practical judgment and engineering discipline to turn ...
Senior Machine Learning Scientist I/II, Model-Driven Optimization
Somerville, MA · On-site
$99K - $136K/yr
The ideal candidate combines depth in probabilistic machine learning, Bayesian optimization, active learning, or related approaches with the practical judgment and engineering discipline to turn ...
Design and coordinate sequential experiment campaigns using Bayesian optimization and active learning, accounting for operational variabilities and constraints. * Select and maintain surrogate models ...
Design and coordinate sequential experiment campaigns using Bayesian optimization and active learning, accounting for operational variabilities and constraints. * Select and maintain surrogate models ...
Design and coordinate sequential experiment campaigns using Bayesian optimization and active learning, accounting for operational variabilities and constraints. * Select and maintain surrogate models ...
Design and coordinate sequential experiment campaigns using Bayesian optimization and active learning, accounting for operational variabilities and constraints. * Select and maintain surrogate models ...
Design and coordinate sequential experiment campaigns using Bayesian optimization and active learning, accounting for operational variabilities and constraints. * Select and maintain surrogate models ...
Design and coordinate sequential experiment campaigns using Bayesian optimization and active learning, accounting for operational variabilities and constraints. * Select and maintain surrogate models ...
Applied Data Scientist
Loveland, CO · 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
Loveland, CO · 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 ...
Chief Textile Scientist
Groton, MA · On-site
... Bayesian optimization to accelerate discovery cycle s. · Communicate findings clearly to senior R&D and executive leadership: what you found, what it means, and just as importantly what you killed ...
Chief Textile Scientist
Groton, MA · On-site
... Bayesian optimization to accelerate discovery cycle s. · Communicate findings clearly to senior R&D and executive leadership: what you found, what it means, and just as importantly what you killed ...
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 ...
Applied AI Research Fellow
Chicago, IL · On-site
We combine sequence-based models and variational autoencoders (VAEs) with Bayesian optimization, using experimental data to rapidly design and refine proteins into impactful therapeutics. The Applied ...
Applied AI Research Fellow
Chicago, IL · On-site
We combine sequence-based models and variational autoencoders (VAEs) with Bayesian optimization, using experimental data to rapidly design and refine proteins into impactful therapeutics. The Applied ...
Applied Data Scientist
Santa Rosa, CA · On-site
$117.75 - $196.25/hr
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
$117.75 - $196.25/hr
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
Loveland, CO · On-site
$117.75 - $196.25/hr
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
Loveland, CO · On-site
$117.75 - $196.25/hr
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 ...
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 ...
AI & modeling: property prediction, design spaces, Bayesian optimization, LLM-augmented optimization Your mission is to translate this tech stack into clear narratives, compelling launches, and ...
AI & modeling: property prediction, design spaces, Bayesian optimization, LLM-augmented optimization Your mission is to translate this tech stack into clear narratives, compelling launches, and ...
Data Scientist
San Francisco, CA · On-site +1
$160K - $200K/yr
Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization), either PhD or Advanced MS degree. * Comfortable with Python, Flask/Django, Pandas and Numpy
Data Scientist
San Francisco, CA · On-site +1
$160K - $200K/yr
Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization), either PhD or Advanced MS degree. * Comfortable with Python, Flask/Django, Pandas and Numpy
Lead adaptive experimentation - contextual bandit systems, Bayesian optimization, automated allocation beyond simple A/B tests. * Drive the platform roadmap with product, design, and data science.
Lead adaptive experimentation - contextual bandit systems, Bayesian optimization, automated allocation beyond simple A/B tests. * Drive the platform roadmap with product, design, and data science.
Lead adaptive experimentation - contextual bandit systems, Bayesian optimization, automated allocation beyond simple A/B tests. * Drive the platform roadmap with product, design, and data science.
Lead adaptive experimentation - contextual bandit systems, Bayesian optimization, automated allocation beyond simple A/B tests. * Drive the platform roadmap with product, design, and data science.
Bayesian Optimization information
What is the difference between Bayesian Optimization vs Data Scientist?
| Aspect | Bayesian Optimization | Data Scientist |
|---|---|---|
| Primary Focus | Optimizing complex functions and hyperparameters | Analyzing data, building models, deriving insights |
| Required Skills | Statistics, probability, machine learning, programming | Statistics, programming, data analysis, visualization |
| Work Environment | Research labs, AI/ML teams, R&D departments | Business, tech companies, consulting firms |
| Common Tools | Python, R, Bayesian libraries (e.g., GPy, scikit-optimize) | Python, R, SQL, visualization tools |
Bayesian Optimization is a specialized technique used within machine learning and AI to efficiently tune hyperparameters or optimize functions. Data Scientists often utilize Bayesian Optimization as part of their toolkit but have broader responsibilities, including data analysis, modeling, and reporting. While Bayesian Optimization focuses on optimization tasks, Data Scientists work on understanding and interpreting data to inform business decisions.
More about Bayesian Optimization jobs
What cities are hiring for Bayesian Optimization jobs?
Cities with the most Bayesian Optimization job openings:
What states have the most Bayesian Optimization jobs?
States with the most job openings for Bayesian Optimization jobs include:
What job categories do people searching Bayesian Optimization jobs look for?
The top searched job categories for Bayesian Optimization jobs are:
Full-time
Re-posted 2 days ago
Hexion rating
7.0
Based on 6 frontline employees who took The Breakroom Quiz
74th of 100 rated chemical manufacturers
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 1989, the company is headquartered in Mount Maunganui, NZL, with a team of 1001-5000 employees. The company is currently Late Stage.
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 1989, the company is headquartered in Mount Maunganui, NZL, with a team of 1001-5000 employees. The company is currently Late Stage.
About Hexion
Sourced by ZipRecruiter
Industry
Chemical manufacturing
Company size
10,000+ Employees
Headquarters location
Columbus, OH, US
Year founded
1899