As a founding team member of Ramp's Risk Data Science team, you will help manage credit and fraud risk effectively. This role will require you to work with unstructured data, leverage logistic regression and machine learning techniques to help develop customer life cycle risk models (acquisitions, customer management, transaction fraud risk, loss forecasting & life time value). The role will also require you to partner with the engineering team to help enhance the data architecture to enable more efficient data mining and model building.
What You’ll Do
- Review internal and external data sources to create custom attributes
- Leverage statistical and machine learning techniques for effective variable selection and model development
- Document model development and validation details for peer review & approval processes
- Partner with Risk Engineering to implement the model and monitor its performance, and make updates as needed
- Partner with Risk Engineering to enhance data architecture to improve efficiency for model building in the future
- Work with leadership to understand priorities, and create a roadmap for model development and deployment
What You Need
- Minimum 3 years of experience in predictive modeling, especially in credit or fraud risk space
- Experience within consumer/corporate cards, payments, lending, or related industries
- Ability to explain complex modeling techniques & results to a diverse audience
- BS/ MS/ PhD in a quantitative field - Applied Mathematics, Statistics, Computer Science, Economics, Engineering, Physics and other related fields
- Strong programming skills (Python, R, SAS, SQL, etc.)
Nice to Haves
- Experience in high growth startups
- Experience building complex financial products
Ramp Benefits
- 100% medical, dental & vision insurance coverage for you
- Partially covered for your dependents
- 401k (including employer match)
- Unlimited PTO
- WFH stipend to support your home office needs
- Monthly wellness stipend
- Annual education reimbursement
- Relocation support