Data Science Tech Lead Data Products at Ramp

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. More than 10,000 customers cut their expenses by 3.5% per year and closing their books 8x faster by switching to the Ramp platform.
Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment software in America and enables billions of dollars of purchases each year. Ramp continues to grow at an increasingly large scale, more than doubling its revenue run rate in the first half of 2022.
Valued at $8.1 billion, Ramp's investors include Founders Fund, Stripe, Citi, Goldman Sachs, Coatue Management, D1 Capital Partners, Redpoint Ventures, General Catalyst, and Thrive Capital, 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 was named Fast Company’s most innovative finance company in 2022.
About the Role
Come lead the future of production data science at Ramp! The Data Science team at Ramp creates value by optimizing core leverage points across the business to enable better insights and build better products. You will build the first iteration of customer facing data products such as price intelligence, merchant categorization, savings insights, and more. Ultimately, you will leverage millions of data points across transactions, users, businesses, and merchants to build the core platforms and services that allow Ramp to save our companies time and money.
You will need to have a head for product development & cross-functional collaboration, since you will partner closely with business stakeholders to prioritize, execute, and drive results. You will also partner closely with the rest of the data team and the engineering team to design, implement, and maintain data science services in production.
What You’ll Do

Full stack data science product development: from project conception, to data modeling and cleaning, to research and prototyping, to deploying and monitoring models in production
Contribute to the company roadmap by working closely with stakeholders throughout the lifecycle of prioritization: from complex and nebulous business context, to well-defined objectives, to a roadmap of scoped opportunities for leveraging data science to drive business results
Architect and define the required technical platforms that enable us to build data science products and services at scale
Manage the upstream and downstream relationships and SLAs with frequent data science collaborators: analytics engineering, data engineering, product engineering, as well as third party vendors and software providers
Lead solutions on tough data science problems around NLP, forecasting, recommendations, human-in-the-loop systems & processes, and more

What You Need

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 Data Scientist, Research Scientist, Machine Learning Engineer, or equivalent
Strong knowledge of SQL (preferably Redshift, Snowflake, BigQuery); experience working with large datasets in Python
Ability to build standalone data science products/services and to work cross-functionally to deploy and monitor in production
Experience with the nuts-and-bolts of machine learning: custom loss functions, stochastic gradient descent, backtesting frameworks, etc
Track record of shipping high quality data products in production and at scale
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 deploying NLP classification, recommendation services in product environments 
Strong perspective on analytics engineering development cycle (data modeling, version control, documentation + testing, best practices for codebase development)
Familiarity with MLOps/infra required to build and scale low latency customer facing data science services experience with Databricks, MLflow, AWS (Sagemaker, Redshift, ECS, Fargate, Load Balancer, EMR) or equivalent
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)

Please note only 401k contributions made while employed by Ramp are eligible for an 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