Description
About the Role:
We are looking for a Staff Data Scientist to build the models that power the credit risk and fraud functions for the Motive Card, a key new focus area for Motive. The Motive Card is a corporate card natively integrated with a fleet management platform, giving businesses an all-in-one solution to automate their financial and physical operations. As a member of our team you’ll help frame the problems, build models and products that win customers, and leverage machine learning at a massive scale to solidify Motive’s technology lead in the connected fleet management space.
Responsibilities:
- Work closely with Risk, Product and Engineering teams to build, improve and implement underwriting and fraud models
- Derive insights from complex data sets to identify credit and fraud risk
- Apply statistical and machine learning techniques on large datasets
- Evaluate the utility of non-traditional data sources
Qualifications:
- Bachelor's degree or higher in a quantitative field, e.g. Computer Science, Math, Economics, or Statistics
- 7+ years experience in data science, machine learning, and data analysis - specifically in the Credit Risk space
- Expertise in applied probability and statistics
- Experience building credit risk and fraud models
- Deep understanding of machine learning techniques and algorithms
- End-to-end deployment data-driven model deployment experienc
- Expertise in data-oriented programming (e.g. SQL) and statistical programming (e.g., Python, R). PySpark experience is a big plus
