Similar Jobs at Motive
Who we are:
Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks.
Motive serves nearly 100,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector.
Visit gomotive.com to learn more.
About the Role:
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.
What You’ll Do:
- 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
What We’re Looking For:
- 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
- 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
Creating a diverse and inclusive workplace is one of Motive’s core values. We are an equal opportunity employer and welcome people of different backgrounds, experiences, abilities and perspectives.
Pay Transparency
Your compensation may be based on several factors, including education, work experience, and certifications. For certain roles, total compensation may include restricted stock units. Motive offers benefits including health, pharmacy, optical and dental care benefits, paid time off, sick time off, short term and long term disability coverage, life insurance as well as 401k contribution (all benefits are subject to eligibility requirements). Learn more about our benefits by visiting Motive Perks & Benefits.
The compensation range for this position will depend on where you reside. For this role, the compensation range is:
Creating a diverse and inclusive workplace is one of Motive's core values. We are an equal opportunity employer and welcome people of different backgrounds, experiences, abilities and perspectives.
Please review our Candidate Privacy Notice here.
UK Candidate Privacy Notice here.
The applicant must be authorized to receive and access those commodities and technologies controlled under U.S. Export Administration Regulations. It is Motive's policy to require that employees be authorized to receive access to Motive products and technology.
#LI-Remote
What you need to know about the Colorado Tech Scene
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
