Industrial Data Scientist: Process Modeling & ML

SMS group Inc; Pittsburgh (Allegheny County); On-site; USD 110,000 - 160,000; Full time

Job summary

SMS group Inc. is seeking a Data Scientist to blend machine learning with process understanding in steel production. You will work with engineers and domain experts to translate process know-how into hybrid models, build virtual sensors, and deploy data-driven solutions into production.

The role emphasizes end-to-end data science delivery, monitoring, and cross-functional collaboration, with on-site work and travel to customer sites as needed.

Qualifications

• Master’s degree or 2+ years in quantitative field with ML focus.
• Proven experience deploying AI/ML solutions in production.
• Ability to collaborate with engineers and domain experts.
• Familiarity with Python, SQL, Git and container tech.
• Strong communication with stakeholders and teams.
• Ability to plan over longer horizons and coordinate work.
• Willingness to work on-site and travel to customer sites.

Responsibilities

• Own data science problems end to end: scoping, data analysis, feature engineering, modeling, validation, deployment.
• Serve as algorithmic lead; select tools and methods; build robust production-ready solutions.
• Monitor model performance, diagnose drift, retrain as needed, and optimise robustness and runtime.
• Collaborate with product/engineering/project teams to align data work with roadmaps.
• Engage with customers to refine solutions and ensure adoption.

Skills

Machine learning

Data interpretation

Communication

Problem solving

Education

Master’s degree in data science or related field

2+ years of relevant experience

Tools

Python

SQL

Git

Docker

TensorFlow/Keras

scikit-learn

Job description

SMS group Inc. is seeking a Data Scientist to blend machine learning with process understanding in steel production. You will work with engineers and domain experts to translate process know-how into hybrid models, build virtual sensors, and deploy data-driven solutions into production.

The role emphasizes end-to-end data science delivery, monitoring, and cross-functional collaboration, with on-site work and travel to customer sites as needed.