Senior Applied Scientist (Credit Risk)

Role Overview

Join Ramp as a Senior Applied Scientist (Credit Risk). You will design, build, and optimize machine learning models that support credit risk decision-making and portfolio management, partnering with business, product, data, and engineering teams to turn ambiguous problems into an actionable applied science roadmap.

Key Responsibilities

• Design, build, and optimize ML models for credit risk decisioning and portfolio management.
• Own the full applied science lifecycle, from:
  • data exploration and feature development
  • model prototyping
  • deployment, monitoring, and iteration
• Investigate and integrate new data sources (structured and unstructured) into credit models when appropriate.
• Translate technical work into clear insights via communication and data narratives to drive strategy.

Requirements

• Strong mathematical foundation in advanced statistics, machine learning, optimization, and/or economics.
• Experience working with large datasets using Python and SQL.
• Strong Python skills across:
  • exploratory data analysis
  • predictive modeling
  • applied machine learning
  • using tools such as NumPy, pandas, scikit-learn, PyTorch (or similar).
• Bachelor’s degree or above in a quantitative field (e.g., Math, Economics, Statistics, Engineering, CS).
• 5+ years of industry experience as an Applied Scientist / ML Engineer / Research Scientist (or 3+ years with a PhD).
• Proven track record of shipping high-quality ML products in production at scale.
• Ability to thrive in a fast-paced startup environment with iterative technical solutions.

Nice to Have

• PhD in a quantitative field.
• Familiarity with data orchestration platforms: Airflow, Dagster, Prefect.
• Strong perspective on the data science engineering development cycle (data modeling, version control, documentation + testing, best practices).
• Experience leveraging AI/LLMs for development or internal workflows.
• Experience at a high-growth startup.

Location / Work Model

• Full remote (New York, US listed).