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Data Science Machine Learning Jobs in Pennsylvania

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 ...

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 ...

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 ...

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

Data Scientist

Philadelphia, PA · On-site

$103K - $173K/yr

Degree in Data Science, Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, or a related quantitative discipline. * Extensive Python programming skills and ...

Data Scientist

Philadelphia, PA · On-site

$103K - $173K/yr

Degree in Data Science, Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, or a related quantitative discipline. * Extensive Python programming skills and ...

Degree in Data Science, Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, or a related quantitative discipline. * Extensive Python programming skills and ...

Degree in Data Science, Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, or a related quantitative discipline. * Extensive Python programming skills and ...

Lead Data Scientist

Philadelphia, PA · On-site

$163K - $173K/yr

Stay current with the latest advancements in data science, machine learning, and generative AI, and encourage a culture of continuous learning, experimentation, and innovation within the team.

This new initiative will involve utilizing data science and machine learning best practices to achieve business objectives, including demand forecasting, pricing, and experimentation. This individual ...

This new initiative will involve utilizing data science and machine learning best practices to achieve business objectives, including demand forecasting, pricing, and experimentation. This individual ...

Data Scientist III

Philadelphia, PA · On-site +1

$110K - $115K/yr

Also required is: 2 years of experience: with doctor, nurse, and patient information needs to design Data Science, Machine Learning (ML) and Natural Language Processing (NLP) solutions to improve ...

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

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

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

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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 Jul 23, 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 are the key skills and qualifications needed to thrive as a Data Science Machine Learning professional, and why are they important?

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.

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.
Infographic showing various Data Science Machine Learning job openings in Pennsylvania as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $123,033 per year, or $59.2 per hour.
Manager Data Science

Manager Data Science

RELX

Philadelphia, PA

$115K - $192K/yr

Other

Posted 11 days ago


Job description

AI for Science, Research Intelligence & Knowledge Discovery

Lead the Teams Building AI That Advances Science

What if the teams you lead could help accelerate scientific breakthroughs, improve healthcare outcomes, and expand human knowledge?

At Elsevier, data science leadership is about far more than managing projects, models, or roadmaps. It is about leading teams that build intelligent systems enabling researchers, clinicians, educators, and institutions to discover evidence, connect ideas, uncover insights, and solve some of the world's most important challenges.

Every day, millions of researchers depend on our products to navigate an ever-growing universe of scientific knowledge. As a Data Science Leader, your work will directly influence how knowledge is discovered, understood, trusted, and applied across the global research ecosystem.

This is leadership with purpose. This is AI in service of science.

About the team

As part of a growing team of Data Scientists, you will take on some of the hardest problems in science. This team is building intelligent systems that can reason across scientific publications, research data, knowledge graphs, ontologies, metadata, taxonomies, citations, and content spanning every scientific discipline.

About the Role

As a Data Science Leader, you will build, develop, and inspire high-performing teams responsible for delivering advanced AI, machine learning, search, retrieval, NLP, and generative AI solutions that power scientific discovery and research intelligence.

You will provide strategic direction, elevate technical excellence, and help shape the future of AI-enabled products used by researchers and healthcare professionals worldwide. Working at the intersection of cutting-edge technology and meaningful impact, you will guide teams solving some of the most complex and intellectually challenging problems in science.

Success in this role requires a balance of technical depth, people leadership, strategic thinking, and a passion for helping others do their best work while advancing a mission that matters.

What You'll Do

  • 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 discovery, research intelligence, and knowledge-access products.
  • Drive the development of AI-powered capabilities across search, retrieval, recommendation, NLP, knowledge systems, and generative AI.
  • Translate complex customer, scientific, and business challenges into scalable data science solutions and measurable outcomes.
  • Establish high standards for experimentation, evaluation, model quality, reliability, and responsible AI practices.
  • Partner closely with Product, Engineering, Research, UX, Analytics, and domain experts to shape product strategy and delivery.
  • Mentor and coach team members while fostering a culture of scientific rigor, collaboration, innovation, and continuous learning.
  • Guide the adoption of emerging AI technologies, including LLMs, retrieval-augmented generation, semantic search, and knowledge-based systems.
  • Influence senior stakeholders and contribute to long-term AI, technology, and product strategy across the organization.
  • Ensure that AI systems are trustworthy, scalable, explainable, measurable, and aligned with meaningful customer and societal outcomes.

What We're Looking For

  • Significant experience leading data science, machine learning, artificial intelligence, NLP, information retrieval, or related technical teams.
  • Proven success building, coaching, and developing high-performing teams in complex technology or product environments.
  • Technical expertise across machine learning, generative AI, large language models, retrieval systems, experimentation, and model evaluation.
  • Experience delivering AI-powered products or platforms from concept through production deployment and measurable impact.
  • Deep understanding of modern AI approaches, including LLMs, RAG architectures, semantic search, embeddings, and knowledge systems.
  • Experience establishing evaluation frameworks, experimentation practices, and performance metrics for AI solutions.
  • Ability to translate ambiguous challenges into clear strategy, execution plans, and business outcomes.
  • Exceptional communication and stakeholder-management skills with the ability to influence technical, product, and executive audiences.
  • Experience working with large-scale structured, semi-structured, and unstructured data in production environments.
  • A passion for advancing science, expanding access to knowledge, developing people, and applying AI to create meaningful real-world impact.

Why Join Elsevier

Because your leadership will matter.

You will lead teams building AI systems that help researchers discover knowledge faster, assess evidence more effectively, generate new insights, and accelerate scientific progress.

U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $121,200 - $201,900.If performed in New York, the base pay range is $126,900 - $211,500.If performed in New York City, the base pay range is $138,400 - $230,700.If performed in Rochester, NY, the base pay range is $115,400 - $192,300.If performed in New Jersey, the base pay range is $136,213 - $217,587. This job is eligible for an annual incentive bonus.

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