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 more than 120,000 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.
What You’ll Do:
- Work closely with Product Insurance to build, improve and implement data ETLs and analysis
- 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
- 5+ years experience in data science, machine learning, and data analysis
- Expertise in SQL and Python
- Expertise in applied probability and statistics
- Deep understanding of machine learning techniques and algorithms
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.
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Motive San Francisco, California, USA Office
Our headquarters are located in the heart of the city’s bustling South of Market (SOMA) neighborhood, a short walk from major public transit lines.
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