Senior Applied Scientist

Motive

57d•Remote

About The Position

We are looking for a Senior Applied Scientist to build the models that power the credit risk and fraud functions for the Motive Card, a key 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.

Requirements

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 experience
Expertise in data-oriented programming (e.g. SQL) and statistical programming (e.g., Python, R). PySpark experience is a big plus

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