Applied Scientist Intern

Join our team as an Applied Scientist Intern, where you will own the entire model lifecycle, leverage state-of-the-art AI, and apply versatile techniques to solve novel problems. You will collaborate closely with product and business leaders to translate models and insights into actionable strategies and user-facing features. This internship offers comprehensive benefits, including medical, dental, and vision insurance, a 401(k) with employer match, unlimited PTO, and relocation support to NYC.

About Ramp

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

Responsibilities

• Own the model lifecycle from data exploration and feature engineering to training, benchmarking, deployment, and monitoring.
• Leverage the latest Large Language Models (LLMs) to solve novel problems and create new product capabilities for customers.
• Partner closely with product and business leaders to translate models and insights into actionable strategy and user-facing features.

Requirements

• Practical Experience: track record of curating datasets and building/evaluating ML models
• B.S., M.S. or Ph.D. Student: currently pursuing a degree in Data Science, Computer Science, Math, Physics, Economics, Statistics, or other quantitative fields with an expected graduation date between Dec 2027 - 2029. Graduate degrees are preferred, but not a must
• Strong ML Fundamentals: solid understanding of the mathematical foundations of machine learning, statistics, probability, and optimization
• 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
• Strong Interest or Experience with AI: curiosity and drive to integrate cutting edge LLMs and agents into applied solutions
• Python Proficiency: good grasp of common Data Science libraries (pandas, scikit-learn, NumPy, PyTorch, etc.)
• Production ML Mindset: knowledge of software engineering best practices applied to ML including version control (Git), testing, and writing maintainable code
• Publications, Projects, or Previous Experience: relevant experience applying AI/ML and demonstrating your passion for the field

Preferred

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