Applied Scientist Intern: End-to-End ML to Drive Value

Ramp; United States; Remote; USD 28,000 - 55,000; Part time

Job summary

Ramp’s Applied Science team seeks an intern to own a project from start to finish, collaborating with engineers, product managers, and business stakeholders to translate complex business needs into ML-driven solutions.

This role emphasizes end-to-end ML work—from data exploration and feature engineering to training, benchmarking, deployment, and monitoring—while exploring LLMs and practical AI applications that create real value for Ramp and its customers.

Qualifications

• Strong ML foundations in mathematics, statistics, probability, and optimization.
• Interest or experience with AI, including LLMs and agents, to build applied solutions.
• Pursuing a degree in a quantitative field with graduation between Dec 2027 and 2029.

Responsibilities

• End-to-End ML: manage the model lifecycle from data exploration to training, benchmarking, deployment, and monitoring.
• State-of-the-Art AI: leverage LLMs to solve novel problems and create product capabilities.
• Versatile Techniques: apply deep learning, gradient boosting, or causal inference as appropriate.
• Rigorous Experimentation: quantify impact with A/B tests and statistical methods.
• Collaborate with product and business leaders to translate models into actionable features.

Skills

ML Fundamentals

AI interest

Strong curiosity

Education

Pursuing quant degree (e.g., Data Science, CS, Math)

Tools

Python

pandas

scikit-learn

Job description

Ramp’s Applied Science team seeks an intern to own a project from start to finish, collaborating with engineers, product managers, and business stakeholders to translate complex business needs into ML-driven solutions.

This role emphasizes end-to-end ML work—from data exploration and feature engineering to training, benchmarking, deployment, and monitoring—while exploring LLMs and practical AI applications that create real value for Ramp and its customers.