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Weekend Data Scientist Deep Learning Jobs in Pennsylvania

RELX

Data Scientist

Philadelphia, PA · On-site

$103K - $173K/yr

Data Scientist Build AI That Accelerates Scientific Discovery Do you want your work to help ... Apply the appropriate combination of classical machine learning, deep learning, retrieval, and ...

Elsevier

Data Scientist

Philadelphia, PA · On-site

$103K - $173K/yr

Data Scientist Build AI That Accelerates Scientific Discovery Do you want your work to help ... Apply the appropriate combination of classical machine learning, deep learning, retrieval, and ...

PPG Industries Inc

Senior Data Scientist

Pittsburgh, PA · On-site

Devising and applying state-of-the-art machine learning, deep learning, and modern AI techniques ... Ph.D. in Data Science, Computer Science, Engineering, Chemistry, Physics, or related field. * 5+ ...

PPG

Senior Data Scientist

Pittsburgh, PA · On-site +1

Devising and applying state-of-the-art machine learning, deep learning, and modern AI techniques ... Ph.D. in Data Science, Computer Science, Engineering, Chemistry, Physics, or related field. * 5+ ...

Cadent

Lead Data Scientist

Philadelphia, PA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Data Scientists collaborate directly with the Business, Product, Data Engineering, DevOps and QA ... deep learning, GraphDB SVMs, time series forecasting etc. to build and evaluate models

Cadent

Lead Data Scientist

Philadelphia, PA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Data Scientists collaborate directly with the Business, Product, Data Engineering, DevOps and QA ... deep learning, GraphDB SVMs, time series forecasting etc. to build and evaluate models

Cadent

Lead Data Scientist

Philadelphia, PA · On-site

$150K - $175K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Data Scientists collaborate directly with the Business, Product, Data Engineering, DevOps and QA ... deep learning, GraphDB SVMs, time series forecasting etc. to build and evaluate models

Cadent

Lead Data Scientist

Philadelphia, PA · On-site

$150K - $175K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Data Scientists collaborate directly with the Business, Product, Data Engineering, DevOps and QA ... deep learning, GraphDB SVMs, time series forecasting etc. to build and evaluate models

Cmu

Data Scientist

Pittsburgh, PA

Experience in predictive modeling, data science, and/or AI & machine learning * Deep understanding of statistical modeling techniques and advanced data analytics * Proficient with at least one ...

Carnegie Mellon University

Data Scientist

Pittsburgh, PA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Experience in predictive modeling, data science, and/or AI & machine learning * Deep understanding of statistical modeling techniques and advanced data analytics * Proficient with at least one ...

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All JobsData Scientist Deep Learning JobsWeekend Data Scientist Deep Learning JobsWeekend Data Scientist Deep Learning Jobs in Pennsylvania

Weekend Data Scientist Deep Learning information

What is the difference between Weekend Data Scientist Deep Learning vs Weekend Data Analyst?

AspectWeekend Data Scientist Deep LearningWeekend Data Analyst
Required CredentialsTypically requires a degree in Data Science, Computer Science, or related fields; knowledge of deep learning frameworksUsually requires a degree in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL, and basic analytics tools
Work EnvironmentOften involves working on complex machine learning models, coding in Python or R, and experimenting with neural networksFocuses on data cleaning, reporting, and visualization, often using Excel, Tableau, or Power BI
Employer & Industry UsageUsed in tech companies, research institutions, and AI-focused startupsCommon in finance, marketing, healthcare, and retail sectors

Weekend Data Scientist Deep Learning roles focus on developing advanced AI models and require programming skills, while Weekend Data Analysts handle data interpretation and reporting. Both roles are valuable but differ in technical complexity and industry application.

What are the most commonly searched types of Data Scientist Deep Learning jobs in Pennsylvania?

The most popular types of Data Scientist Deep Learning jobs in Pennsylvania are:

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For Weekend Data Scientist Deep Learning jobs in Pennsylvania, the most frequently searched job titles are:

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Cities in Pennsylvania with the most Weekend Data Scientist Deep Learning job openings:

Weekend Data Scientist Deep Learning jobs near you

Data Scientist- Process Modeling & Machine Learning

The SMS Group

Pittsburgh, PA • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Posted 3 days ago

New

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.
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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.

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