Applied Science Intern: Build ML Solutions for Smart Finance

RAMP; New York; On-site; USD 140,000 - 160,000; Part time

Benefits offered by this job

Apple MacBook

Catered lunches in NYC

Weekly coffee stipend

Housing stipend

Job summary

Ramp is seeking an Applied Science intern in New York to join a hands-on, integrated team and own a project from start to finish. You’ll translate complex business needs into scalable ML solutions, collaborating with engineers, product managers, and stakeholders to deliver real value.

You will focus on problems in credit, fraud, growth, or core product, applying ML concretely, shipping code, and learning how to drive impact in a fast-paced fintech environment.

Qualifications

• Pursuing a degree in Data Science, CS, Math, Physics, Economics, Statistics or similar with graduation Dec 2027–2029.
• Strong foundations in ML, statistics, probability and optimization.
• Curiosity about integrating AI/LLMs into applied solutions.
• Proficiency in Python and DS libraries; SQL in modern warehouses.
• Track record of curating datasets and building ML models.

Responsibilities

• End-to-end ML lifecycle from data exploration to deployment and monitoring.
• Apply state-of-the-art AI/LLMs to new product capabilities.
• Use diverse techniques like deep learning, gradient boosting, causal inference.
• Quantify impact via A/B tests and statistics.
• Collaborate with product and business leaders to translate models into features.

Skills

Python proficiency

ML fundamentals

SQL knowledge

Data science libraries

Strong communication

Bias for action

Practical ML experience

Interest in AI/LLMs

Education

B.S./M.S./Ph.D. student in quantitative field

Tools

Snowflake

BigQuery

Redshift

ClickHouse

Job description

Ramp is seeking an Applied Science intern in New York to join a hands-on, integrated team and own a project from start to finish. You’ll translate complex business needs into scalable ML solutions, collaborating with engineers, product managers, and stakeholders to deliver real value.

You will focus on problems in credit, fraud, growth, or core product, applying ML concretely, shipping code, and learning how to drive impact in a fast-paced fintech environment.