Data Science Intern - Summer 2027

Rippling · San Francisco, CA · по договорённости

Компания
Rippling
Город
San Francisco, CA
Зарплата
по договорённости
Уровень
intern
Формат
internship
Иностранная компания
нанимает русскоязычных

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 2027 (May-August) to work shoulder to shoulder with seasoned data scientists and engineers focused on increasing the impact of Rippling’s product, go-to-market, risk, finance, and operations teams.
Rippling interns gain experience doing the work of full-time data scientists, including building data products, machine learning models, AI-assisted analytics workflows, and production pipelines. Projects are meaningful to the business and scoped so interns can see the full impact of their work.
During your 12 weeks at Rippling, we will provide the tools, mentorship, and context you need to be successful. Your dedicated mentor and manager will support your learning and development, and you will join fellow interns for socials, leader talks, and opportunities to learn how a fast-growing company operates.
What you will do
Use machine learning, statistical analysis, and AI-assisted workflows to analyze customer and product data, uncover insights, and support better decisions.
Design, build, and evaluate predictive models for customer revenue, behavior, retention, risk, and product adoption.
Prototype responsible uses of generative AI, LLMs, or other AI techniques that improve analysis quality, decision support, automation, or user experience.
Build and deploy data and ML pipelines that deliver reliable predictions, recommendations, or insights at scale.
Evaluate model and AI system performance with clear metrics, thoughtful validation, and attention to accuracy, bias, reliability, and business impact.
Actively participate in team meetings to scope, drive, and communicate progress on your projects.
Present your work, methods, tradeoffs, and recommendations to Data Science, R&D, and business leaders.
Build relationships with your intern cohort and learn from executives and teams across Rippling.
What you will need
Currently enrolled in a Bachelor’s or Master’s degree in data science, statistics, computer science, economics, engineering, mathematics, or a related quantitative field, with at least one semester or quarter remaining after the internship.
Previous internship, co-op, research, or project experience in data science, analytics, machine learning, AI, or a related technical area.
Strong programming skills, especially in SQL and Python.
Experience working with data analysis or machine learning tools such as pandas, scikit-learn, PyTorch, TensorFlow, notebooks, dbt, or similar frameworks.
Familiarity with modern AI concepts such as LLM prompting, embeddings, model evaluation, or responsible AI practices.
Excellent communication skills, including the ability to explain technical work, assumptions, and recommendations to technical and non-technical audiences.
Ability to adapt quickly, get your hands dirty with industrial- and startup-grade code and systems, and make pragmatic tradeoffs in ambiguity.
Passion and drive to constantly learn and develop your data science, engineering, and product judgment. 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 l

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