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Internship Data Science R Jobs in Philadelphia, PA

UHS

Applied Data Scientist

King Of Prussia, PA · On-site

The Applied Data Scientist r ecommends and implements methodologies appropriate to large scale data analytics, including those commonly involved in large-scale Machine Learning (ML) and Artificial ...

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All JobsData Science R JobsInternship Data Science R JobsInternship Data Science R Jobs in Philadelphia, PA

Internship Data Science R information

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$12

$22

$42

How much do internship data science r jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for internship data science r in Philadelphia, PA is $22.71, according to ZipRecruiter salary data. Most workers in this role earn between $17.45 and $24.76 per hour, depending on experience, location, and employer.

What types of projects can I expect to work on during a Data Science Internship at R?

As a Data Science intern at R, you will typically be involved in projects such as data cleaning, exploratory data analysis, and building predictive models under the guidance of experienced data scientists. You may also contribute to developing data visualizations and presenting insights to stakeholders. Interns often collaborate with cross-functional teams, including software engineers and business analysts, which provides valuable exposure to real-world data challenges and team-based problem solving.

What is the difference between Internship Data Science R vs Data Analyst Intern?

AspectInternship Data Science RData Analyst Intern
Required SkillsProficiency in R, statistical analysis, data visualizationExcel, SQL, basic statistical knowledge
Work EnvironmentData science teams, research projects, analytics departmentsBusiness units, marketing, finance, or operations teams
Industry UsageTech, finance, healthcare, research institutionsRetail, marketing, consulting, finance

Internship Data Science R focuses on applying R programming for statistical analysis and data modeling, often in research or technical environments. Data Analyst Internships emphasize data cleaning, visualization, and reporting using tools like Excel and SQL. Both roles require analytical skills but differ in technical depth and industry focus.

What is an Internship Data Science R?

An Internship Data Science R is a temporary position for students or recent graduates to gain practical experience in data science, with a focus on using the R programming language. Interns typically work under the guidance of experienced data scientists, assisting with data cleaning, analysis, visualization, and possibly building statistical models. This role helps interns develop technical and analytical skills, and provides exposure to real-world data-driven projects, often found in industries like finance, healthcare, or technology.

What are the key skills and qualifications needed to thrive as an Internship Data Science R, and why are they important?

To thrive as an Internship Data Science R, you need a solid grounding in statistics, data analysis, and programming with R, typically supported by coursework or a degree in a quantitative field. Familiarity with R packages (like tidyverse, ggplot2), data visualization tools, and version control systems such as Git is often required. Strong problem-solving skills, attention to detail, and effective communication help interns translate data insights into actionable recommendations. These abilities are crucial for supporting data-driven decision-making and contributing meaningfully to project teams in a professional environment.
What cities near Philadelphia, PA are hiring for Internship Data Science R jobs? Cities near Philadelphia, PA with the most Internship Data Science R job openings:
Internship Data Science R jobs near you
Infographic showing various Internship Data Science R job openings in Philadelphia, PA as of June 2026, with employment types broken down into 5% Internship, 79% Full Time, 5% Part Time, and 11% Temporary. Highlights an 74% In-person, 21% Hybrid, and 5% Remote job distribution, with an average salary of $47,235 per year, or $22.7 per hour.
Data Science Vice President - Card Data Analytics

Data Science Vice President - Card Data Analytics

JP Morgan Chase

Wilmington, DE • On-site

Full-time

Medical, Retirement

Posted 4 days ago

JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 468 frontline employees who took The Breakroom Quiz

46th of 141 rated banks

Job description

You can help shape how data and AI drive decisions across our Credit Card business. You will work on high-impact problems end-to-end-translating business questions into analytical approaches, building models and solutions, and communicating insights that influence strategy and outcomes. Join a collaborative team where your work can directly improve customer and business experiences through responsible, scalable analytics.

As a Data Science Vice President at JPMorganChase within the Card Data & Analytics team, you will develop analytics and AI/ML solutions that support strategic initiatives and measurable business impact. You will partner across the Card organization to define problems, scope solutions, and deliver high-quality analytical products. You will combine consulting, data science, and programming to drive data science and analytics strategies and deliver actionable insights.

Job responsibilities

  • Leverage experience and analytical skills to uncover novel use cases of Big Data analytics, including opportunities to responsibly apply foundation models and Generative AI
  • Drive data science and analytics strategies, including recommendations on analytical products and standards
  • Help partners define business problems and scope analytical solutions
  • Build an understanding of problem domains and available data assets
  • Research, design, implement, and evaluate analytical approaches and models, including Generative AI-based methods
  • Perform exploratory statistics and data mining tasks on diverse datasets
  • Communicate findings and obstacles to stakeholders to drive delivery to market
  • Develop subject matter expertise in financial and operational domains
  • Code solutions using strong programming skills
  • Collaborate across teams to deliver the best solutions for clients

Required qualifications, capabilities and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Bachelor's degree in a relevant quantitative field and 5+ years of data analytics experience, or advanced degree and 2+ years of experience
  • Exceptional analytical, quantitative, problem-solving, and communication skills
  • Intellectual curiosity for solving business problems
  • Leadership and collaboration skills
  • Knowledge of statistical software (for example, Python, R, SAS) and data querying languages (for example, SQL)
  • Familiarity with Generative AI and prompt engineering basics (prompt design, evaluation, guardrails)
  • Experience with modern analytics tools (for example, SAS, SQL, Hive, Hadoop, Spark, Python, Tableau, Alteryx)
  • Ability to convey complex information to technical and non-technical audiences

Preferred qualifications, capabilities and skills

  • Experience with large language model-enabled applications such as retrieval-augmented generation, classification or extraction from unstructured text, or agent-like workflows; exposure to evaluation methods for quality, cost, and latency
  • Understanding of key drivers within the credit card profit and loss statement
  • Financial services background
  • Master of Science degree or equivalent

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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