Description:
We have access to a virtually unlimited amount of data and we use it to create crucial impact - through timely catching critical incidents and providing actionable insights to Fleet Managers to help them improve their driver safety.
- Analyze an extensive stream of telematics data and strategize on ways to further improve detection risky behavior or how to get better at catching a certain type of collision and making required changes to bring that to fruition.
- Watching out for and addressing any customer concerns that may arise
- Monitor dashboards to ensure everything is working as expected.
What We're Looking For:
- Bachelor's degree or higher in a quantitative field, e.g. Computer Science, Math, Physics or Statistics
- 4+ years experience in data science, machine learning and data analysis
- Expertise in applied probability and statistics
- Deep understanding of machine learning techniques and algorithms
- Experience building outlier detection algorithms
- End-to-end data-driven model deployment experience
- Expertise in data-oriented programming (e.g. SQL) and statistical programming (e.g., Python, R).
- Master's Degree in a relevant field
- Experience in signal processing
- Experience working with telematics data
- Background in Physics based research
- PySpark experience is a plus.