Description:

Motive is seeking a Staff Data Scientist to develop models for the credit risk and fraud functions associated with the Motive Card.
The Motive Card is a corporate card integrated with a fleet management platform, providing businesses with a comprehensive solution for automating financial and physical operations.
The role involves collaborating with Risk, Product, and Engineering teams to build, enhance, and implement underwriting and fraud models.
Responsibilities include deriving insights from complex data sets to identify credit and fraud risks, applying statistical and machine learning techniques on large datasets, and evaluating the utility of non-traditional data sources.

Requirements:

A Bachelor's degree or higher in a quantitative field such as Computer Science, Math, Economics, or Statistics is required.
Candidates must have 7+ years of experience in data science, machine learning, and data analysis, specifically in the Credit Risk domain.
Expertise in applied probability and statistics is essential.
Experience in building credit risk and fraud models is necessary.
A deep understanding of machine learning techniques and algorithms is required.
Candidates should have end-to-end deployment experience in data-driven model deployment.
Proficiency in data-oriented programming (e.g., SQL) and statistical programming (e.g., Python, R) is required, with PySpark experience being a significant plus.

Motive is committed to creating a diverse and inclusive workplace, welcoming individuals from various backgrounds, experiences, abilities, and perspectives.
The company is an equal opportunity employer, ensuring fair treatment for all applicants.
Employees must be authorized to receive and access commodities and technologies controlled under U.S. Export Administration Regulations.