Agero is working with leading vehicle manufacturers, insurance carriers and roadside service providers to drive the next generation of vehicle and mobile technology forward. Our mission is to transform the entire driving experience -- and save lives in the process -- through an unmatched combination of innovative technology and human-powered solutions. These include breakthrough mobile apps designed to bring added safety and convenience to drivers everywhere.
The Data Science Engineering group at Agero focuses on end-to-end algorithm development and production implementation. We get to see our solutions working on large scale (PB) datasets running through consumer facing apps in real-time, and to know that our algorithms are bringing emergency vehicles and roadside service providers to stranded drivers quickly and efficiently. We strive to stay at the forefront of both algorithm and software technology advances and are continuously expanding our skill sets as new solutions emerge. Our group is looking for new team members to help us in our endeavors make the roads a safer place to be.
Your Roles and Responsibilities:
- Research and experiment with data science technologies, discover opportunities for new data analytics features, and influence digital product and technology strategies for the company.
- Develop algorithms (statistical modeling, machine learning, optimization, etc.) to assess driver telematics data and gain new insights into both driver behavior / crash risk and roadside service procedures / efficiencies.
- Communicate research results effectively in written and spoken forms to various audiences including product management, engineering, executives, and customers.
- Drive algorithm implementation at scale through use of technologies such as AWS Lambda or Spark.
- Work in a fast-paced, team-based environment on shared code repositories.
- Represent the organization and advocate its data analytics efforts and capabilities using external presentations and publications.
- 5+ years of experience or PhD in technical field.
- Strong skills to manipulate and clean real-world data (preferably in Python).
- Proficient coding skills (preferably in Python).
- Solid understanding of relevant theories in probability theory, statistics, machine learning, data structure and algorithms, optimization, etc.
- Strong skills to implement statistical modeling and machine learning algorithms (preferably in Python).
- Good communication skills both in written (technical documents, Python notebooks) and spoken (meetings, presentations) forms.
- Willing and able to learn and meet business needs.
- Independent, self-organizing, and able to prioritize multiple complex assignments.
- Experience with AWS technologies including Lambda, DynamoDB, S3, EC2, Redshift.
- Experience using Git and working on shared code repositories.
- Experience with Spark / Databricks.
- Experience implementing and maintaining algorithms in a production environment.