Data Scientist Visa Sponsorship Jobs in Pennsylvania
Pennsylvania's data scientist job market is anchored by Philadelphia's finance and healthcare sectors, Pittsburgh's growing tech and AI research ecosystem, and major employers like Comcast, UPMC, and the University of Pennsylvania. Demand for sponsorship-eligible data scientists is strong across insurance, biopharma, and academic research institutions throughout the state.
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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.
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.
Data Scientist Job Roles in Pennsylvania
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Search Data Scientist Jobs in PennsylvaniaData Scientist Jobs in Pennsylvania: Frequently Asked Questions
Which companies sponsor visas for data scientists in Pennsylvania?
Large employers with consistent data scientist sponsorship records in Pennsylvania include Comcast, UPMC, Independence Blue Cross, SEI Investments, and GSK's North American operations in the Philadelphia area. In Pittsburgh, Carnegie Mellon University affiliates, PNC Financial, and a growing number of AI-focused startups have sponsored data science roles. Consulting firms with Pennsylvania offices, such as Deloitte and Accenture, also file regularly for data science positions.
Which cities in Pennsylvania have the most data scientist sponsorship jobs?
Philadelphia and Pittsburgh account for the large majority of data scientist sponsorship activity in Pennsylvania. Philadelphia draws demand from healthcare systems, insurance companies, and financial services firms, while Pittsburgh's strength comes from its AI research community, university ties, and autonomous vehicle sector. Harrisburg and the broader southeastern Pennsylvania corridor also see sponsorship activity from government contractors and life sciences companies.
Which visa types are most common for data scientist roles in Pennsylvania?
The H-1B visa is by far the most common visa category used to sponsor data scientists in Pennsylvania, given that the role consistently qualifies as a specialty occupation requiring at least a bachelor's degree in a directly related field like statistics, computer science, or data science. Some candidates with advanced degrees pursue the EB-2 immigrant visa pathway. International students completing degrees at Pennsylvania universities sometimes begin on OPT or STEM OPT before employer H-1B sponsorship.
How to find data scientist visa sponsorship jobs in Pennsylvania?
Migrate Mate filters job listings specifically for visa sponsorship eligibility, making it straightforward to browse data scientist roles in Pennsylvania without sifting through positions that won't support international candidates. You can filter by state and role to surface active openings from Pennsylvania employers who have a track record of sponsoring H-1B and other work visas for data science positions in cities like Philadelphia and Pittsburgh.
Are there any Pennsylvania-specific factors data scientists should know about visa sponsorship?
Pennsylvania's dense concentration of research universities, including Penn, Carnegie Mellon, Drexel, and Pitt, creates strong pipelines that employers are accustomed to hiring from, including international graduates. The Department of Labor's prevailing wage requirements apply statewide, and wages for data scientist roles in Philadelphia and Pittsburgh are generally benchmarked against those metro areas separately. Healthcare and financial services employers in the state tend to have established immigration legal teams, which can make the sponsorship process more structured than at smaller firms.
What is the prevailing wage for sponsored data scientist jobs in Pennsylvania?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.