Data Scientist- Process Modeling & Machine Learning

Posted 8 Days Ago
Pittsburgh, PA, USA
In-Office
Junior
Other
The Role
Develop hybrid, process-informed ML models and virtual sensors with process engineers; own end-to-end data science from feature engineering to production deployment, monitoring, and maintenance; engage customers and cross-functional teams for adoption.
Summary Generated by Built In

Data Scientist- Process Modeling & Machine Learning

Summary

We are seeking a Data Scientist who combines strong machine learning expertise with a genuine understanding of the processes behind the data. In this role, you will collaborate closely with process engineers and domain experts to understand how our machinery and production processes behave and apply that knowledge to develop models. The central focus of the position is enhancing our existing process models with data-driven techniques and machine learning. By integrating domain knowledge with advanced modeling methods, you will build solutions that perform robustly in production and earn the confidence of the engineers, operators, and customers who depend on them.

Who we are

At SMS group, our people are our greatest asset. We offer an entrepreneurial environment that promotes a culture of innovation, growth, and inclusion. We offer company events, activities, and opportunities to participate in charitable initiatives that benefit the communities where we are located. 

www.sms-group.us

What you’ll do

Process Understanding & Domain Collaboration

  • Partner closely with process engineers, metallurgists, and domain experts to develop a deep, working understanding of the underlying processes and the data they generate.
  • Translate process know-how into model structure — constraints, features, and
  • relationships — rather than treating the process as a black box.
  • Spend time where the data comes from: participate in site visits to connect raw signals to real physical behavior.

Hybrid & Process-Informed Modeling

  • Enhance existing process models with data-driven techniques, replacing weak assumptions or unmodeled effects with learned components while preserving the physics that already works.
  • Design and implement hybrid models that combine domain/first-principles sub-models with machine learning (gray-box, physics-informed, and residual-modeling approaches).
  • Develop virtual/soft sensors to estimate quantities that are hard or expensive to measure directly.

End-to-End Data Science Delivery

  • Own data science problems end to end: scoping, data analysis (time-series and relational), feature engineering, modeling, validation, and deployment into production.
  • Serve as the algorithmic point of contact for your solutions, choosing the right tool for the problem — robust feature-based methods (e.g., scikit-learn) as well as deep learning (e.g., TensorFlow/Keras) where it adds value.
  • Build engineering prototypes and turn promising experiments into reliable, maintainable production solutions.

Production, Monitoring & Maintenance

  • Monitor model performance on live data, diagnose drift, and retrain or recalibrate as conditions change.
  • Continuously optimize and maintain deployed solutions to improve accuracy, robustness, and runtime performance. 

Collaboration & Adoption 

  • Work with cross-functional teams (product, engineering, project management) to align data science work with product roadmaps and project goals. 
  • Engage with customers to gather feedback, refine solutions, and ensure that data-driven approaches are accepted and adopted by the people who use them.


What you’ll need

Required

  • Master’s degree in data science, Machine Learning, Statistics, Applied Mathematics, a quantitative engineering discipline (e.g., process modeling, mechanical, control), or a related field - or 2+ years of relevant experience. 
  • Proven experience taking AI/ML solutions into real production environments (not just notebooks and prototypes). 
  • Demonstrated ability to understand a problem domain and incorporate that understanding into models - comfort working alongside engineers and domain experts and learning the underlying process. 
  • Understanding of software development practices: Python, SQL, Git, code review, and familiarity with container technologies. 
  • Strong communication skills for working with other departments, customers, and stakeholders, and the ability to explain technical choices to non-specialists. 
  • Ability to plan over longer horizons and coordinate work packages effectively. 
  • Willingness to work on-site at the office and to travel to customer sites. 

Preferred 

  • Hands-on experience with hybrid / gray-box / physics-informed modeling, or with enhancing first-principles or simulation models using data-driven methods. 
  • Experience building virtual/soft sensors, digital twins, or model-based monitoring for industrial or physical processes. 
  • Proficiency with deep learning methods and frameworks. 
  • Background in or exposure to an industrial / manufacturing / process domain (steel, metals, chemical, energy, or similar). 
  • Experience researching and benchmarking existing solutions and algorithms before building from scratch. 

Benefits and Opportunities

  • Open and Collaborative Culture: Work in a flat hierarchy where honest feedback and direct communication are valued. Join an international team and participate in bi-weekly company-wide open Fridays to discuss new tools, technologies, and approaches. 
  • Professional Development: Contribute to scientific papers, collaborate with renowned research institutes on long-term projects, and access company-supported learning opportunities. 
  • Real-World Impact: Have the opportunity to visit customer sites and witness the impact of your work on large machinery and steel production processes. 
  • Continuous Learning: Engage in everyday learning opportunities, regular data science meetings, and paper discussions to stay updated on projects and scientific developments in data science and metallurgy. 
  • Contributing to Industry Standards: Play an integral role in setting digitalization standards for the metals industry.

What we offer

  • Competitive compensation, medical/dental/vision coverage, paid vacation, paid holiday time, 401k with a company match, training, a tuition reimbursement program and more!

What we do

SMS group is the leading partner in the world of metals. We are an original equipment supplier offering comprehensive maintenance and spare part services for metals production, continuous casting and rolling (flat and long products), tubes, welded pipes, forging, non-ferrous technology, and heat treatment plants - all from a single source.

SMS group Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, religion, national origin, age, sexual orientation, disability, veteran status, gender identity or other categories protected by law. Employment is contingent upon successful completion of a drug screen and physical capacity profile test. 

Skills Required

  • Master's degree in data science, ML, statistics, applied math, quantitative engineering, or related field OR 2+ years relevant experience
  • Proven experience deploying AI/ML solutions to production (beyond notebooks/prototypes)
  • Ability to understand problem domains and incorporate domain knowledge into models working alongside engineers and domain experts
  • Understanding of software development practices: Python, SQL, Git, code review, and familiarity with container technologies
  • Strong communication skills to explain technical choices to non-specialists and work with stakeholders
  • Ability to plan over longer horizons and coordinate work packages effectively
  • Willingness to work on-site at the office and travel to customer sites
  • Hands-on experience with hybrid/gray-box/physics-informed modeling or enhancing first-principles models with data-driven methods
  • Experience building virtual/soft sensors, digital twins, or model-based monitoring for industrial/physical processes
  • Proficiency with deep learning methods and frameworks
  • Background or exposure to industrial/manufacturing/process domains (steel, metals, chemical, energy, or similar)
  • Experience researching and benchmarking existing solutions and algorithms before building from scratch
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The Company
HQ: Pittsburgh, PA
755 Employees

What We Do

SMS group Inc. is responsible for new equipment sales, upgrades and modernizations for North American metals producers, and is a world leader in outsourced maintenance services for the steel and non-ferrous metals industry. SMS group Inc., a member of the SMS group family, is headquartered in Pittsburgh, Pennsylvania. At SMS group Inc., we are an original equipment supplier offering comprehensive maintenance and spare part services for metals production, continuous casting and rolling (flat and long products), tubes, welded pipes, forging, non-ferrous technology, and heat treatment plants - all from a single source. Apart from traditional refurbishment services for all major OEM equipment, you can also take advantage of our comprehensive field services and modernization projects. Steel production is our largest market, where we supply world class new equipment and actively support operations and maintenance devising solutions throughout the process from melting and casting to rolling and finishing. In addition to new equipment supply, our Forging division has experienced maintenance specialists who focus on closed and open-die forging, powder metal presses, extrusion presses, and ring rolling. New equipment supply, maintenance services, and spare parts inside the aluminum industry crosses a wide variety of products including flat rolling mill equipment, plate stretchers and extrusion presses. For tubes and pipes, our unique broad know-how covers the complete line of processes from ERW to spiral welded pipe as well as seamless producing operations utilizing equipment from cold drawing and pilger mills to piercing mills. It is our commitment to be the Leading Partner for our customers guiding and assisting our customers to make equipment and process decisions that allow them to remain competitive in an ever evolving global market, and serve as a single source for new equipment, maintenance and spare parts that our customers can trust and value.

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