Hybrid Data Scientist: Physics-Informed Process Modeling

SMS group; Pittsburgh (Allegheny County); On-site; USD 120,000 - 165,000; Full time

Benefits offered by this job

401k with company match

Tuition reimbursement

Medical/dental/vision coverage

Job summary

SMS group is seeking a Data Scientist to combine machine learning with process knowledge in a manufacturing setting. You will work closely with process engineers and domain experts to translate domain know-how into robust, data-driven models that perform in production and earn the trust of engineers, operators, and customers.

The role emphasizes end-to-end delivery from data analysis through deployment, with a focus on hybrid modeling, virtual sensors, and continuous monitoring of performance in

Qualifications

• Master’s degree in data science, ML, statistics, applied mathematics or related field, or 2+ years of relevant experience.
• Proven experience deploying AI/ML solutions in production environments.
• Ability to understand a problem domain and collaborate with engineers/domain experts.

Responsibilities

• Understand processes with process engineers and domain experts to model data-driven solutions.
• Develop hybrid/physics-informed models blending first-principles with machine learning.
• Lead end-to-end data science projects from data analysis and feature engineering to deployment.
• Monitor model performance in production and retrain as conditions change.
• Collaborate with cross-functional teams and engage with customers to drive adoption.

Skills

Python

SQL

Git

Containerization

Production ML

Domain collaboration

Communication

Education

Master’s degree / 2+ years exp

Tools

scikit-learn

TensorFlow

Keras

Pandas

Job description

SMS group is seeking a Data Scientist to combine machine learning with process knowledge in a manufacturing setting. You will work closely with process engineers and domain experts to translate domain know-how into robust, data-driven models that perform in production and earn the trust of engineers, operators, and customers.

The role emphasizes end-to-end delivery from data analysis through deployment, with a focus on hybrid modeling, virtual sensors, and continuous monitoring of performance in