Ramp is a financial operations platform designed to save businesses time and money. Combining corporate cards with expense management, bill payments, vendor management, accounting automation, and more, Ramp's all-in-one solution frees finance teams to do the best work of their lives. More than 25,000 companies, from family-owned farms to e-commerce giants to space startups, have saved $1B and 10M hours with Ramp. Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment platform in America, and enables over 35 billion dollars in purchases each year.
Ramp's investors include Sequoia, Founders Fund, Thrive Capital, Khosla Ventures, Greylock, Stripe, Goldman Sachs, Coatue, and Redpoint, as well as over 100 angel investors who were founders or executives of leading companies. The Ramp team comprises talented leaders from leading financial services and fintech companies—Stripe, Affirm, Goldman Sachs, American Express, Mastercard, Visa, Capital One—as well as technology companies such as Meta, Uber, Netflix, Twitter, Dropbox, and Instacart.
Ramp has been named to Fast Company's Most Innovative Companies list and LinkedIn's Top U.S. Startups for over 3 years, as well as the Forbes Cloud 100 , CNBC Disruptor 50 , and TIME Magazine's 100 Most Influential Companies .
We’re seeking someone to lead the future of identity machine learning at Ramp. In this role, you will help build core machine learning, design data architectures, and set strategic roadmaps to help Ramp reduce Identity-related threats. You will partner closely with product and engineering counterparts across model design, implementation, execution, and analysis. Our goal is to provide a frictionless experience for every legitimate Ramp user.
Employ statistical and machine learning on large datasets to discover patterns of account takeovers and identity theft
Prototype and productionalize machine learning models and rules-based systems to protect user accounts
Partner closely with Identity Engineering and Data Platform teams to augment and leverage data across first and third party sources, ensuring we’ve added as much context as possible to every decision we make
Contribute to the culture of Ramp’s machine learning team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way
Bachelor’s degree or above in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields with a minimum of 5 years of industry experience as a Machine Learning Engineer, Applied Scientist or Data Scientist
Strong python experience (numpy, pandas, sklearn, pytorch etc.) across ML techniques and back end engineering
Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems
Strong knowledge of SQL (preferably Snowflake, BigQuery)
Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions
Context on Fraud and/or Identity Threat detection systems
Experience at a high-growth startup
Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Census or equivalents)
Strong perspective on data science engineering development cycle (data modeling, version control, documentation + testing, best practices for codebase development)
100% medical, dental & vision insurance coverage for you
401k (including employer match on contributions made while employed by Ramp)
Flexible PTO
Fertility HRA (up to $5,000 per year)
WFH stipend to support your home office needs
Wellness stipend
Parental Leave
Relocation support to NYC or SF
Pet insurance
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
$185K – $315K • Offers Equity
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