Data Science Intern - Summer 2027

RipplingRipplingSan Francisco, California, United States
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Posted

9/21/2026

Employment

Intern

Range

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Work style

Hybrid

3 days in office

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AI summary

Core responsibilities

The intern will use machine learning and data mining techniques to analyze customer data and generate actionable insights for business decisions. They will also build and deploy end-to-end machine learning pipelines to forecast revenue and customer behavior.

Requirements overview

Candidates must be currently enrolled in a Bachelor's or Master's degree program in data science or a related field with at least one semester remaining after the internship. Applicants should have previous internship or co-op experience in data science and possess strong programming skills in SQL and Python.

Key skills

Data scienceMachine learningSQLPythonData miningPredictive modelingData analysisPipeline deploymentRevenue forecastingCustomer insightsEngineeringCommunication

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Education requirements

bachelor degreepostgraduate degree

About Rippling

Industry

Software Development

Employees

7,863

Type

Privately Held

Size

1,001-5,000 employees

Rippling is a workforce management system that eliminates the friction from running a business. Today, most companies struggle with everything from routine tasks, like running payroll, to cross-functional planning, like aligning on headcount. That’s because all their data related to people, processes, and systems is scattered in a hundred places. Rippling has every application you need to run your business—from applicant tracking and payroll to IT and expenses—in one place. But unlike other systems, Rippling sits on top of a unified platform. Data flows dynamically between Rippling’s applications, giving every team a shared source of truth, the power to automate processes, and access to the insights they need. This allows your business to execute better, faster. Based in San Francisco, CA, Rippling has raised $1.2B from the world’s top investors—including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock. Get help: rippling.com/contact Licensing details: https://app.rippling.com/licensing

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Job categories

Data & AnalyticsTechnologySoftwareScience & Research

Description

About the role Here at Rippling, we believe in our early talent’s potential, experience and aspirations. Our mission is to create opportunities for students through mentorship and training, ownership through impactful projects, and, of course, fun through our dynamic startup culture. As a Data Science Intern, you will join our Data Science Team in Summer 2026 (May-August) to work shoulder to shoulder with a team of seasoned data scientists and analysts dedicated to boosting the impact of all Rippling’s motions, be it in product, sales, marketing, risk, or financial investments. Rippling Interns gain the experience of full-time data scientists including building machine learning (ML) models and deploying end to end production pipelines. Interns will be assigned projects that not only have an impact on the business, but that are also scoped to fit within the time constraints of their internship so they can see the full impact of their work. During your 13 weeks at Rippling, we will provide all of the tools needed to be successful. Your dedicated mentor and manager will provide support for your learning and development throughout your time with us. You will join your fellow interns in a variety of socials, talks with Rippling leaders, and more! What you will do Use machine learning and other data mining techniques to analyze customer data and uncover customer level insights that help drive GTM decisions and improve Product Design, build, and deploy models to forecast multiple components of customer revenue and behavior, creating a valuable outlook for future revenue and customer success Deploy end to end ML pipelines to deliver prediction and insights at scale Actively participate in team meetings to scope, drive, and progress your projects Present your work to our R&D senior team Attend Meet & Greets with various executives and teams to gain a holistic view of what it takes to run a company like Rippling What you will need Previous internship/co-op experience in data science Currently enrolled in a Bachelor’s or Master's degree in data science or in a related field with at least 1 semester/quarter after their internship is completed Excellent communication skills Solid programming skills with an emphasis on SQL and Python Ability to adapt get your hands dirty with both industrial- and startup grade code and systems Passion and drive to constantly learn and develop your engineering skills Even if you don’t meet all of the requirements listed here, we still encourage you to apply. Skills can be used in lots of different ways and your life and professional experience may be relevant beyond what our list of requirements has outlined. Additional Information Rippling is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics, Rippling is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email accomodations@rippling.com Rippling highly values having employees working in-office to foster a collaborative work environment and company culture. For office-based employees (employees who live within a 40 mile radius of a Rippling office), Rippling considers working in the office, at least three days a week under current policy, to be an essential function of the employee's role. Interns will be based out of one of our San Francisco and New York offices.

Requirements

  • Data science
  • Machine learning
  • SQL
  • Python
  • Data mining
  • Predictive modeling
  • Data analysis
  • Pipeline deployment
  • Revenue forecasting
  • Customer insights
  • Engineering
  • Communication

Benefits

  • Mentorship
  • Training
  • Social events

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