About Ramp
Ramp is the ultimate platform for modern finance teams. Combining corporate cards with expense management, bill payments, vendor management, accounting automation and more, Ramp's all-in-one solution is designed to save businesses time and money, and free finance teams to do the best work of their lives. Our mission is to help build healthier businesses, and it’s working: over 25,000 businesses on Ramp to save an average 5% and close their books 8x faster.
Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment platform in America, and enables tens of billions of dollars in purchases each year.
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. In 2023, Ramp was named Fast Company’s #1 Most Innovative Company in North America, LinkedIn’s #1 Top Startup in the U.S., a CNBC Disruptor, and a TIME100 Most Influential Company.
About the Role
We’re looking for someone to help lead the future of credit applied science at Ramp. The Applied Science team at Ramp creates value by building the models powering decision-making. You will need to have a head for strategy & cross-functional collaboration, since you will partner closely with business & product 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 models in production.
Applied scientists at Ramp focuses on solving quantitative problems across credit, fraud, growth, and our core product by applying the right mix of causal inference, structural modeling, and optimization.
What You’ll Do
Full stack data science development: from upstream 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
Leverage a combination of causal inference, structural modeling and optimization to build key models to solve core business problems
Formulate backtesting frameworks to empirically validate model performance
Generate and communicate data-driven insights to influence decision making across Ramp
What You Need
Bachelor’s degree or above in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields
For candidates with Bachelors and Master’s, minimum of 7 years of industry experience as a Data Scientist, Research Scientist, or equivalent. For candidates with Doctor Degree, minimum of 3 years of industry experience
Strong familiarity with the mathematical fundamentals of advanced statistics, optimization, and/or economics, as well as methods for experimental design and causal inference
Experience working with large datasets in Python, Strong knowledge of SQL (preferably Redshift, Snowflake, BigQuery)
Strong python experience (numpy, pandas, sklearn, pytorch etc.) across exploratory data analysis, predictive modeling, and applications of ML techniques
Strong communication: the ability to bridge technical methodology to meaningful data narratives to drive company decisions and strategy
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
Strong perspective on data science engineering development cycle (data modeling, version control, documentation + testing, best practices for codebase development)
Familiarity with data orchestration platforms (Airflow, Dagster, Prefect)
Experience at a high-growth startup
Benefits (for U.S.-based full-time employees)
100% medical, dental & vision insurance coverage for you
Partially covered for your dependents
One Medical annual membership
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 for NY
Pet insurance
Other notices
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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