Ramp
Applied Scientist Intern
New York, NY (HQ) · Hybrid · Internship · Posted Sep 15, 2026
- Education
- Currently pursuing a B.S., M.S., or Ph.D. in Data Science, Computer Science, Math, Physics, Economics, Statistics, or another quantitative field; expected graduation between Dec 2027 - 2029.
About the job
Build and deploy machine-learning solutions for Ramp’s finance products, owning projects from data exploration through monitoring and measuring their impact.
What you'll do
- Own the model lifecycle, including feature engineering, training, benchmarking, deployment, and monitoring.
- Apply LLMs and other ML techniques, and evaluate impact through A/B tests and statistical methods.
- Collaborate with product and business partners to turn models and insights into strategy and user-facing features.
What they ask for
- Currently pursuing a B.S., M.S., or Ph.D. in a quantitative field, with expected graduation between Dec 2027 - 2029.
- Strong foundations in machine learning, statistics, probability, and optimization.
- Python proficiency and experience with common data science libraries; SQL knowledge and experience working with a modern data warehouse.
- Track record of curating datasets and building or evaluating ML models.
Nice to have
- Graduate degrees are preferred.
- Relevant AI/ML publications, projects, or experience; production ML practices or data orchestration experience.
Pay
$12,500 USD per month (internship rate; housing stipend also stated, amount unspecified)
Tools
Python, pandas, scikit-learn, NumPy, PyTorch, Snowflake, BigQuery, Redshift
AI focus
Use LLMs and agents, alongside other machine-learning methods, to develop applied solutions and new product capabilities.
Model-written summary · the original posting is authoritative