Summary

About the Role

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. 

What You’ll Do

1. Employ statistical and machine learning on large datasets to discover patterns of account takeovers and identity theft
2. Prototype and productionalize machine learning models and rules-based systems to protect user accounts
3. 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
4. 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

What You Need

1. 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
2. Strong python experience (numpy, pandas, sklearn, pytorch etc.) across ML techniques and back end engineering
3. Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems
4. Strong knowledge of SQL (preferably Snowflake, BigQuery)
5. Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions

Nice-to-Haves

1. Context on Fraud and/or Identity Threat detection systems
2. Experience at a high-growth startup
3. Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Census or equivalents)
4. Strong perspective on data science engineering development cycle (data modeling, version control, documentation + testing, best practices for codebase development)

Skills

• Database Management
• Machine Learning
• Software Engineering
• SQL