Ramp is looking to solve critical business problems through the development of machine learning models and tools, aiming to improve underwriting, combat fraud, and enhance spend management.
Requirements
- 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
- 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
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 our customers
- apply the right tools to the right problems, whether it’s deep learning, gradient boosting, or causal inference
- quantify the impact of your work through A/B tests and other statistical methods
- partner closely with product and business leaders to translate models and insights into actionable strategy and user-facing features
Other
- 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 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
- Relocation support to NYC or SF (as needed)
