Machine Learning Data Scientist

Company Overview

Imagine Everything. Build the Future with Hexion.

At Hexion, we push boundaries, rethink possibilities, and create real impact. We activate science to deliver progress—developing breakthrough solutions that strengthen industries, protect communities, and drive a more sustainable future.

This is where bold thinkers, problem-solvers, and innovators come together to shape what’s next. Whether you're engineering advanced materials, transforming manufacturing technologies, or leading strategic innovation, your ideas and actions leave a lasting mark. We cultivate an inclusive culture of growth, collaboration, and accountability, ensuring every contribution propels us forward.

We don’t follow the status quo—we challenge it, disrupt it, and improve it. Every role at Hexion is part of something bigger.

We invest in innovation, sustainability, and continuous development—equipping you with the tools, training, and opportunities to excel. With an unwavering commitment to safety, partnership, belonging, and impact, we empower you to lead change and strengthen industries worldwide.

Your Future Starts Here.  

If you’re ready to push limits, reimagine what’s possible, and create the extraordinary, Hexion is where you belong. 

Anything is possible when you imagine everything. 

About the Role

We are seeking a Machine Learning Data Scientist to join our applied research team, where we develop real-time decision-making and recommendation systems for industrial production lines. You'll be responsible for developing robust and interpretable machine learning models that transform complex sensor data into actionable insights. 

This role requires a strong mix of analytical thinking, practical ML experience, and the ability to work with real-world, noisy datasets. You'll collaborate closely with deep learning researchers, research engineers, and domain experts to design experiments, evaluate model performance, and bring impactful solutions to production. 

Job Responsibilities

• Design, train, and evaluate machine learning models (e.g., classification, regression, clustering, ranking) for real-time industrial applications. 
• Engineer meaningful features from raw sensor and control data. 
• Analyze large-scale datasets to uncover patterns, define KPIs, and guide algorithm development. 
• Validate model assumptions, monitor performance over time, and detect model drift or anomalies. 
• Work with data engineers to define data requirements and prepare clean, structured datasets. 
• Collaborate with research engineers to operationalize ML models in production environments. 
• Document findings and present insights to both technical and non-technical stakeholders.

Minimum Qualifications

• B.Sc./M.Sc. in Computer Science, Statistics, Applied Mathematics, or related field. 
• 5+ years of experience applying machine learning to real-world problems. 
• Strong skills in Python and ML libraries such as scikit-learn, XGBoost, LightGBM, or CatBoost. 
• Experience with feature engineering, model selection, hyperparameter tuning, and evaluation techniques. 
• Solid understanding of statistics, data distributions, and uncertainty estimation. 
• Hands-on experience working with messy, high-dimensional, or time-series data. 

Preferred Qualifications

• Background in industrial, sensor-based, or time-series prediction problems. 
• Familiarity with anomaly detection and root cause analysis. 
• Experience working closely with MLOps or deploying models to production. 
• Comfort working in fast-paced environments with evolving data and priorities