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