ZipRecruiter

Log In

1

Data Science Machine Learning Jobs in Pennsylvania

TeleTracking

Machine Learning Engineer III

Pittsburgh, PA · On-site

$111K - $133K/yr

... data scientists, software engineers, clinicians, hospital administrators, and experts in TeleTracking Technologies to identify and develop high-impact machine learning solutions. • Work with large ...

Elsevier

Manager Data Science

Philadelphia, PA · On-site

$115K - $192K/yr

Lead and develop high-performing teams of data scientists, machine learning engineers, researchers, and technical contributors. * Define and execute data science strategies that advance scientific ...

Elsevier

Manager Data Science

Philadelphia, PA · On-site

$115K - $192K/yr

Lead and develop high-performing teams of data scientists, machine learning engineers, researchers, and technical contributors. * Define and execute data science strategies that advance scientific ...

RELX

Manager Data Science

Philadelphia, PA

$115K - $192K/yr

Lead and develop high-performing teams of data scientists, machine learning engineers, researchers, and technical contributors. * Define and execute data science strategies that advance scientific ...

RELX Group plc

Manager Data Science

Philadelphia, PA · On-site

$115K - $192K/yr

Lead and develop high-performing teams of data scientists, machine learning engineers, researchers, and technical contributors. * Define and execute data science strategies that advance scientific ...

The Pennsylvania State University

POSITION SPECIFICS We are seeking a Senior Data Engineer with deep expertise in database design, optimization, and data access strategies to support our growing data science and machine learning ...

RELX Group plc

Senior Data Scientist

Philadelphia, PA · On-site

Significant hands-on experience in Data Science, Machine Learning, Artificial Intelligence, NLP, Information Retrieval, Statistics, Computer Science, or a related quantitative discipline. * Advanced ...

next page

Showing results 1-20

All JobsData Science Machine Learning JobsData Science Machine Learning Jobs in Pennsylvania

Data Science Machine Learning information

See Pennsylvania salary details

$37.6K

$123K

$197K

How much do data science machine learning jobs pay per year?

As of Sep 2, 2026, the average yearly pay for data science machine learning in Pennsylvania is $123,033.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,700.00 and $136,300.00 per year, depending on experience, location, and employer.

What is data science machine learning?

Data science machine learning refers to the use of algorithms and statistical models to analyze and draw insights from complex data sets. In this field, professionals use machine learning techniques to build predictive models, automate decision-making processes, and uncover patterns in data. Machine learning is a core component of data science, enabling systems to improve their performance over time without being explicitly programmed. Data scientists with machine learning expertise are in high demand across industries like healthcare, finance, and technology.

What are the key skills and qualifications needed to thrive as a data science machine learning professional?

To thrive as a Data Science Machine Learning professional, you need a strong background in statistics, programming (usually Python or R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications such as AWS Certified Machine Learning, are typically valuable. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These skills enable professionals to develop robust models, extract actionable insights, and drive data-driven decision-making in organizations.

What are some common challenges faced when deploying machine learning models as a data science machine learning professional?

A frequent challenge in this role is bridging the gap between building accurate models in a controlled environment and deploying them effectively in production systems. Issues such as data drift, model performance degradation, and integration with existing IT infrastructure often arise. Collaboration with engineering and IT teams is crucial to ensure models are scalable, maintainable, and secure. Regular monitoring and updating of deployed models are also essential responsibilities to sustain their value to the business.

What is the difference between Data Science Machine Learning vs Data Analyst?

AspectData Science Machine LearningData Analyst
Required SkillsProgramming (Python, R), statistics, machine learning algorithmsData visualization, SQL, basic statistics
Work EnvironmentDeveloping models, coding, experimenting with algorithmsData reporting, dashboard creation, data cleaning
Industry UsageTech, finance, healthcare, where predictive models are neededBusiness intelligence, marketing, operations

Data Science Machine Learning professionals focus on building predictive models and algorithms using programming and advanced statistics, often working on complex projects. Data Analysts primarily interpret data through visualization and reporting to support business decisions. While both roles require data skills, Data Science Machine Learning involves more technical programming and modeling, whereas Data Analysts focus on data interpretation and presentation.

Is data science machine learning a high paying job?

Data science and machine learning roles are generally high-paying within the tech industry due to the specialized skills required, such as programming, statistical analysis, and experience with tools like Python or TensorFlow. Salaries vary based on experience, location, and company size but tend to be above average compared to many other professions.
Data Science Machine Learning jobs near you
Infographic showing various Data Science Machine Learning job openings in Pennsylvania as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $123,033 per year, or $59.2 per hour.

Data Scientist- Process Modeling & Machine Learning

SMS group Inc

Pittsburgh, PA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 11 days ago

Job description

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.