Applied Scientist Intern
Core
Building models and tools for underwriting, fraud detection, and spend management using machine learning and LLMs.
Role type
Applied Science Intern (Machine Learning)
Builds
Scalable ML-driven solutions for credit, fraud, and growth
Domain
Fintech / Financial Services
Deliverable
production ML models
Required skills
Machine learning fundamentals, Python, SQL, LLMs, deep learning, gradient boosting, causal inference, data exploration, feature engineering, model deployment, A/B testing
Preferred skills
Data orchestration, software engineering best practices, publications, previous AI/ML projects
Technologies
PyTorch, pandas, scikit-learn, NumPy, Snowflake, BigQuery, Redshift, Clickhouse, Git, Airflow, Dagster, Prefect, Metaflow (via careerplan.io/jobs/b39ceb08-a0a7-4f8b-a760-2fb88e209956-applied-scientist-intern-at-ramp)
Responsibilities
Own the model lifecycle from data exploration to monitoring, leverage LLMs for novel problems, apply diverse ML techniques, quantify impact via A/B tests, collaborate with product and business leaders
Seniority
Intern
