Experience in applied statistics and uncertainty quantification, including model calibration and domain of validity. * Strong Python skills and experience with mainstream Python-based ML frameworks ...
Experience in applied statistics and uncertainty quantification, including model calibration and domain of validity. * Strong Python skills and experience with mainstream Python-based ML frameworks ...
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 ...
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 uncertainty quantification, with emphasis on calibrated posteriors that drive acquisition. • Strong Python skills and experience with mainstream Python-based ML and Bayesian optimization ...
... and uncertainty quantification, with emphasis on calibrated posteriors that drive acquisition. • Strong Python skills and experience with mainstream Python-based ML and Bayesian 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 ...
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 ...
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 ...
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 ...
Experience in applied statistics and uncertainty quantification, including model calibration and domain of validity. * Strong Python skills and experience with mainstream Python-based ML frameworks ...
Experience in applied statistics and uncertainty quantification, including model calibration and domain of validity. * Strong Python skills and experience with mainstream Python-based ML frameworks ...
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 ...
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 ...
Experience in applied statistics and uncertainty quantification, including model calibration and domain of validity. * Strong Python skills and experience with mainstream Python-based ML frameworks ...
Experience in applied statistics and uncertainty quantification, including model calibration and domain of validity. * Strong Python skills and experience with mainstream Python-based ML frameworks ...
Experience in applied statistics and uncertainty quantification, including model calibration and domain of validity. * Strong Python skills and experience with mainstream Python-based ML frameworks ...
Experience in applied statistics and uncertainty quantification, including model calibration and domain of validity. * Strong Python skills and experience with mainstream Python-based ML frameworks ...
Uncertainty Quantification information
See salary details
$30K - $38.3K
11% of jobs
$45.7K is the 25th percentile. Wages below this are outliers.
$38.3K - $46.5K
16% of jobs
$46.5K - $54.8K
11% of jobs
The median wage is $61K / yr.
$54.8K - $63.1K
17% of jobs
$63.1K - $71.4K
9% of jobs
$79.3K is the 75th percentile. Wages above this are outliers.
$71.4K - $79.6K
13% of jobs
$79.6K - $87.9K
10% of jobs
$87.9K - $96.2K
3% of jobs
$96.2K - $104.5K
3% of jobs
$104.5K - $112.7K
5% of jobs
$112.7K - $121K
3% of jobs
$30K
$69.5K
$121K
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For Uncertainty Quantification jobs, the most frequently searched job titles are:
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The top searched job categories for Uncertainty Quantification jobs are:
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Cities with the most Uncertainty Quantification job openings:
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States with the most job openings for Uncertainty Quantification jobs include:

Applied ML Scientist - Chemistry
Columbus, OH • On-site
Other
Re-posted 16 days ago
Hexion rating
7.0
Based on 6 frontline employees who took The Breakroom Quiz
75th of 104 rated chemical manufacturers
Job description
- Lead ML model development for prediction and optimization across chemistry, formulation, property, and process.
- Collaborate with R&D and manufacturing on problem framing and translate business goals into well-posed multi-objective optimization modeling tasks.
- Curate and analyze chemical and experimental data, assessing quality and structure and the limits it places on modeling.
- Develop and select input representations for raw materials, chemistry, and signal data, such as molecular descriptors and fingerprints, learned embeddings, and spectral features.
- Select, train, and evaluate models across families such as regression, tree ensembles, Gaussian processes, neural networks including physics-informed architectures, and chemistry foundation models.
- Quantify and calibrate model performance and uncertainty, and define each model’s domain of validity for downstream use.
- Apply transfer learning to make use of multiple data sources, such as related tasks, prior campaigns, and data of varying fidelity and completeness.
- Explore and adopt emerging ML methods, including LLM and agentic approaches, to advance modeling.
- Communicate methods, results, and their limitations clearly to technical and non-technical audiences.
- Bachelor’s degree in Computer Science, Data Science, Computational Chemistry, Cheminformatics, or a related field, with substantial relevant experience in ML modeling experience for chemistry, formulation, process, or manufacturing problems.
- Domain knowledge in chemistry, preferably polymer chemistry.
- Demonstrated ability to develop molecular and materials representations and to select, train, and evaluate predictive models across families.
- Experience in applied statistics and uncertainty quantification, including model calibration and domain of validity.
- Strong Python skills and experience with mainstream Python-based ML 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.
- Master’s degree in Computer Science, Data Science, Computational Chemistry, Cheminformatics, or a related field.
- 5+ years experience.
- Experience with cheminformatics, chemistry foundation models and physics-informed modeling.
- Familiarity with active learning, Bayesian optimization, and related techniques.
- Knowledge of ML engineering core tasks and techniques, such as data and optimization pipelines, model deployment, and MLOps.
We are an Equal Opportunity, Affymative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law.
Nearest Major Market: Columbus
Nearest Secondary Market: Dublin
About Hexion
Sourced by ZipRecruiter
Industry
Chemical manufacturing
Company size
10,000+ Employees
Headquarters location
Columbus, OH, US
Year founded
1899