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Data Scientist Machine Learning Jobs (NOW HIRING)

Koantek

Data Scientist

Chandler, AZ · On-site

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong ... Build and optimize machine learning models for classification, regression, predictive analytics ...

Koantek

Data Scientist

Chandler, AZ

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong ... Build and optimize machine learning models for classification, regression, predictive analytics ...

Quince

Senior Data Scientist, Growth

Palo Alto, CA

THE ROLE Data Scientist, Growth We are seeking a Data Scientist, Growth to join our growing team ... Build end-to-end production machine learning models from 0 to 1 with immediate, high-visibility ...

Nestle

Senior Data Scientist

Bridgewater, NJ

Analyze large and complex datasets to identify patterns, build statistical and machine learning ... Integrate the latest data science innovations into product solutions, enhancing data, analytical ...

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

As of Aug 6, 2026, the average yearly pay for data scientist machine learning in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a data scientist machine learning?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the data scientist machine learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

What are the typical day-to-day responsibilities of a data scientist machine learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

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DATA Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist- Process Modeling & Machine Learning

SMS group Inc

Pittsburgh, PA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 15 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.