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Internship Graduate Machine Learning Jobs in Philadelphia, PA

Strong foundation in statistics and machine learning concepts (regression, classification ... Previous internship or project experience demonstrating practical data science applications.

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Internship Graduate Machine Learning information

See Philadelphia, PA salary details

$25.7K

$43K

$88.8K

How much do internship graduate machine learning jobs pay per year?

As of Aug 20, 2026, the average yearly pay for internship graduate machine learning in Philadelphia, PA is $42,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,800.00 and $46,400.00 per year, depending on experience, location, and employer.

What is an internship graduate machine learning?

Internship Graduate Machine Learning positions are entry-level roles designed for recent graduates or students who have completed coursework in machine learning, data science, or related fields. These internships provide hands-on experience working with real-world data, building and testing machine learning models, and collaborating with experienced professionals. Interns gain exposure to industry-standard tools and techniques, helping them bridge the gap between academic learning and practical application. Such positions are valuable for building a portfolio, networking, and enhancing job prospects in the rapidly growing field of artificial intelligence.

What types of projects do internship graduate machine learning roles typically involve, and how are responsibilities structured within the team?

Internship Graduate Machine Learning roles often focus on supporting ongoing research or development projects, such as building predictive models, cleaning and analyzing data, or prototyping algorithms. Interns usually collaborate closely with data scientists and engineers, contributing to specific project milestones while learning best practices in model development and deployment. Responsibilities are often structured to allow for mentorship and feedback, with interns participating in regular team meetings, code reviews, and brainstorming sessions. This collaborative environment provides valuable exposure to real-world machine learning workflows and helps interns build both technical and soft skills relevant to the field.

What are the key skills and qualifications needed to thrive as an internship graduate machine learning, and why are they important?

To thrive as an Internship Graduate in Machine Learning, you typically need a strong background in mathematics, programming (especially Python), and familiarity with algorithms and data structures, often supported by coursework or a degree in computer science, statistics, or a related field. Hands-on experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of tools such as Jupyter Notebooks and version control systems like Git, are highly valued. Curiosity, problem-solving, teamwork, and effective communication are crucial soft skills to excel in collaborative and innovative environments. These competencies enable interns to contribute to real-world projects, adapt to fast-changing technologies, and communicate findings clearly within interdisciplinary teams.

What is the difference between Internship Graduate Machine Learning vs Data Analyst?

AspectInternship Graduate Machine LearningData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; basic knowledge of programming and statisticsDegree in Statistics, Mathematics, or related field; proficiency in data visualization and analysis tools
Work EnvironmentTech companies, research labs, startups; project-based, collaborative teamsBusiness, finance, marketing sectors; focus on reporting and data interpretation
Employer & Industry UsageUsed in tech, AI, and research industries for developing machine learning modelsCommon in corporate, finance, and consulting firms for data-driven decision making

While both roles involve working with data, an Internship Graduate Machine Learning focuses on developing algorithms and models using programming skills, often in tech environments. In contrast, a Data Analyst emphasizes interpreting data, creating reports, and supporting business decisions. The roles overlap in data handling but differ in technical depth and application focus.

Infographic showing various Internship Graduate Machine Learning job openings in Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,971 per year, or $20.7 per hour.

Quantitative Research Internship - PhD: Summer 2027

Susquehanna International Group

Bala Cynwyd, PA โ€ข On-site

Other

Posted 16 days ago


Job description

Overview
As a Quantitative Research Intern at Susquehanna, you will work on projects that model the work of our full-time employees. You will also go through a comprehensive education program and interact with mentors who are at the top of their field, allowing you to build foundational knowledge in quantitative finance. You will have the opportunity to build alphas on an actual trading strategy.
What you can expect
  • Modelling: Apply probability theory, statistical analysis, and machine learning techniques to predict market behavior and generate alphas
  • Execution: Create strategies to execute on modelling ideas under simulated competition
  • Evaluation: Backtest ideas using historical market data and revise strategies
  • Breadth: Explore all aspects of quant work and different areas of Susquehanna's business
  • Education: Participate in a comprehensive education program and receive personalized mentorship from experienced professionals to accelerate your growth
  • Collaboration: Work in an open environment that allows you to collaborate with multiple teams and get exposure to different groups and parts of the business
Susquehanna combines all of the above to provide the best quant internship program in the industry. Join us to see why so many previous quant interns decide to return for a full-time career.
What we're looking for
  • PhDs (in penultimate or final year) in quantitative fields such as mathematics, physics, statistics, electrical engineering, computer science, operations research, or economics
  • Analytical problem-solvers with excellent logical reasoning and a passion for turning data into decisions
  • Clear communicators in a fast-paced and highly collaborative environment
  • Programmers comfortable processing and analyzing large data sets in Python; experience with C++ (or another low-level language) is a plus
  • Strategic thinkers with demonstrated interests in strategic games and/or competitive activities
  • Self-motivated and quick to learn, thriving in dynamic, fast-moving environment

By applying to this role, you will be automatically considered for the Quantitative Systematic Trading Internship program. There is no need to apply to both positions to be considered for both.
About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.
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