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Summer 2026 | Applied Scientist Intern

Ramp

New York City, NY, USA Remote internship

Posted: September 10, 2025

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Job Description

ABOUT RAMP

At Ramp, we’re rethinking how modern finance teams function in the age of AI. We believe AI isn’t just the next big wave. It’s the new foundation for how business gets done. We’re investing in that future — and in the people bold enough to build it.

Ramp is a financial operations platform designed to save companies time and money. Our all-in-one solution combines payments, corporate cards, vendor management, procurement, travel booking, and automated bookkeeping with built-in intelligence to maximize the impact of every dollar and hour spent. More than 50,000 businesses, from family-owned farms to e-commerce giants to space startups, have saved $10B and 27.5M hours with Ramp. Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment platform in America, and enables over $100 billion in purchases each year.

Ramp’s investors include Lightspeed Venture Partners, Thrive Capital, Sands Capital, General Catalyst, Founders Fund, Khosla Ventures, Sequoia Capital, Greylock, Redpoint, and ICONIQ, as well as over 100 angel investors who were founders or executives of leading companies. The Ramp team comprises talented leaders from leading financial services and fintech companies—Stripe, Affirm, Goldman Sachs, American Express, Mastercard, Visa, Capital One—as well as technology companies such as Meta, Uber, Netflix, Twitter, Dropbox, and Instacart.

Ramp has been named to Fast Company’s Most Innovative Companies https://www.fastcompany.com/91038883/ramp-most-innovative-companies-2024 list and LinkedIn’s Top U.S. Startups https://www.linkedin.com/pulse/linkedin-top-startups-2024-50-us-companies-rise-linkedin-news-hxote/?trackingId=uBI29YlAOxikbTI7cdvG4g%3D%3D for more than 3 years, as well as the Forbes Cloud 100 https://www.forbes.com/sites/richardnieva/2024/08/06/ramp-cloud-100/, CNBC Disruptor 50 https://www.cnbc.com/2024/05/14/ramp-cnbc-disruptor-50.html, and TIME Magazine’s 100 Most Influential Companies https://time.com/collection/time100-companies-2023/6285147/ramp/.


ABOUT THE ROLE

The Applied Science team builds models and tools that solve Ramp’s most critical problems: from underwriting businesses to combatting fraud to making spend management smarter. We’re deeply embedded in the business and provide a quantitative foundation for decision making.

As an Applied Science intern, you’ll be a fully integrated member of the team and own your project from start to finish. Working with engineers, product managers, and business stakeholders, you’ll translate complex business needs into scalable machine-learning-driven solutions. This is a chance to apply ML concretely, ship code, and create genuine value for Ramp and our customers.

You'll focus on exciting problems in areas like: credit, fraud, growth, or our core product!


WHAT YOU’LL DO

- End-to-End ML: own the model lifecycle from data exploration and feature engineering to training, benchmarking, deployment, and monitoring

- State-of-the-Art AI: leverage the latest Large Language Models (LLMs) to solve novel problems and create new product capabilities for our customers

- Versatile Techniques: apply the right tools to the right problems, whether it’s deep learning, gradient boosting, or causal inference

- Rigorous Experimentation: quantify the impact of your work through A/B tests and other statistical methods

- Collaborate: partner closely with product and business leaders to translate models and insights into actionable strategy and user-facing features


WHAT YOU NEED

- M.S. or Ph.D. Student: currently pursuing degree in Data Science, Computer Science, Math, Physics, Economics, Statistics, or other quantitative fields with an expected graduation date between Dec 2026 - 2027

- Strong ML Fundamentals: solid understanding of the mathematical foundations of machine learning, statistics, probability, and optimization

- Python Proficiency: good grasp of common Data Science libraries (pandas, scikit-learn, NumPy, PyTorch, etc.)

- SQL Knowledge: experience wrangling data in a modern data warehouse (e.g. Snowflake, BigQuery, Redshift, Clickhouse)

- Practical Experience: track record of curating datasets and building/evaluating ML models

- Interest or Experience with AI: curiosity and drive to integrate cutting edge LLMs and agents into applied solutions

- Strong Communication: ability to clearly explain complex concepts to both technical and non-technical audiences and use data to build a compelling narrative

- Bias For Action: a comfort with ambiguity and desire to ship solutions quickly then iterate


NICE TO HAVES

- Publications, Projects, or Previous Experience: relevant experience applying AI/ML and demonstrating your passion for the field

- Production ML Mindset: knowledge of software engineering best practices applied to ML including version control (Git), testing, and writing maintainable code

- Data Orchestration: experience with leveraging modern data orchestration platforms (Airflow, Dagster, Prefect, Metaflow)


COMPENSATION

- The monthly rate for this internship is $11,375 USD + $10k housing stipend


RAMP BENEFITS

- Apple MacBook

- Catered lunches in NYC office Monday-Friday

- Weekly coffee stipend


BENEFITS (FOR U.S.-BASED FULL-TIME EMPLOYEES)

- 100% medical, dental & vision insurance coverage for you

- Partially covered for your dependents

- One Medical annual membership

- 401k (including employer match on contributions made while employed by Ramp)

- Flexible PTO

- Fertility HRA (up to $5,000 per year)

- WFH stipend to support your home office needs

- Wellness stipend

- Parental Leave

- Relocation support to NYC or SF (as needed)

- Pet insurance


REFERRAL INSTRUCTIONS

If you are being referred for the role, please contact that person to apply on your behalf.


OTHER NOTICES

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

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