Ramp is building the next generation of finance tools—from corporate cards and expense management, to bill payments and accounting integrations—designed to save businesses time and money with every click. Over 5000 businesses are spending an average of 3.3% less and closing their books 8 times faster, thanks to Ramp’s finance automation platform that enables billions of dollars of purchases each year.

Founded in 2019, Ramp has seen nearly 10x year-over-year growth which has led to a valuation of $8.1 billion in just over 3 years. Its investors include Founders Fund, Stripe, Citi, Goldman Sachs, Coatue Management, D1 Capital Partners, Redpoint Ventures and Thrive Capital, as well as over 100 angel investors who were founders or executives of leading companies. The team is made up of talented leaders from some of the leading financial services and fintech companies—Capital One, Stripe, Affirm, Goldman Sachs, American Express, Visa—as well as high-growth technology companies like Facebook, Spotify, Zendesk, Uber, Dropbox, and Instacart. Recently named Fast Company’s most innovative finance company, Ramp is NYC’s fastest-growing startup and America’s fastest-growing corporate card.

About the Role

Come lead the future of Risk Analytics at Ramp! You will lead and grow the risk data science and analytics engineering teams, develop the roadmap on reporting, data science products, experimental design, and be responsible for building the platforms and services necessary to support a best-in-class Risk Analytics org. You will partner closely with the Risk Operations team to improve how Ramp makes decisions around underwriting, fraud, experimental design, capital markets, and more. You will partner closely with Risk Engineering on product, data infrastructure, systems design, and how to deploy data science models in production. Ultimately, you will enable Ramp to get 1% better every day by leveraging data to make better decisions and build better products.

What You’ll Do

• Build, lead, develop, and accelerate Ramp’s risk data science and analytics engineering teams
• Leverage a variety of first and third party data sources to improve how Ramp thinks about underwriting businesses, detecting fraud, pricing new offerings, and ongoing risk management.
• Full stack data science development: from upstream data modeling and cleaning, to research and prototyping, to deploying and monitoring models in production
• Develop the company roadmap by working closely with stakeholders throughout the lifecycle of prioritization: from complex business context, to well-defined objectives, to a roadmap of scoped opportunities for leveraging data science to drive business results
• Design systems and SLAs that allow risk analytics to capture, move, store, and transform raw data into highly actionable insights with product and data engineering teams
• Contribute to Ramp’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way

What You Need

• Minimum 2 years of data science management management experience
• Proven leadership of teams that ship high quality data products in production and at scale
• Strong perspective on analytics engineering development cycle (data modeling, version control, documentation and unit testing, best practices for codebase development)
• Strong perspective on data science development cycle (problem definition, EDA + feature engineering, modeling + evaluation, deploy + monitor + iterate in production)
• Strong familiarity with the mathematical fundamentals of advanced statistics, optimization, and/or economics
• Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions

Nice to Haves

• PhD in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields
• Experience with consumer or business credit and fraud modeling
• Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Census or equivalents) and data orchestration platforms (Airflow, Dagster, Prefect)
• Familiarity with MLOps/infra required to support data science product solutions
• Familiarity and experience with methods for experimental design and causal inference
• Experience at a high-growth startup

Ramp Benefits (for U.S. based employees)

• 100% medical, dental & vision insurance coverage for you
  • Partially covered for your dependents
  • OneMedical annual membership
• 401k (including employer match)
• Unlimited PTO
• Annual education reimbursement
• WFH stipend to support your home office needs
• Monthly wellness stipend; Headspace annual membership
• Parental Leave
• Relocation support