Data Scientist - Process Modeling & Machine Learning

SMS group is a partner and equipment supplier for metals production and related industrial technologies. The Data Scientist will combine process knowledge, machine learning, and data-driven techniques to enhance process models, develop digital solutions, and deploy reliable production systems. The role also involves collaboration with engineers, customers, and cross-functional teams, as well as monitoring, commissioning, and maintaining solutions.

What you'll do:

• 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
• 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
• 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
• 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
• 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 they're looking for:

• Master's degree in data science, Machine Learning, Statistics, Applied Mathematics, a quantitative engineering discipline (e.g., process, 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
• 1-2 years of experience in applied artificial intelligence technologies including machine learning, predictive data analytics, or data science BE/B. Tech or Advanced degree in a relevant field (Computer Science, Operations Research, Statistics, Mathematics, Electrical Engineering, or other Computational Science)
• Demonstrated ability to iteratively conceptualize, design, and build data-driven analytical models
• Some solid experience applying advanced AI techniques (machine learning, predictive analytics, optimization, semantic analysis, time-series analysis, advanced visualization) to real-world problems
• Strong capabilities in modern analytics languages/tools
• Collaborative, open, and respectful working style

Benefits:

• An entrepreneurial environment that promotes a culture of innovation, growth, and inclusion.
• Company events and activities.
• Opportunities to participate in charitable initiatives that benefit the communities where we are located.
• Medical, dental, and vision coverage.
• Paid vacation.
• Paid holiday time.
• 401k with a company match.
• Training.
• A tuition reimbursement program.