The R&D Team is researching advanced technologies in the Connected and Automated Vehicle domain.
You will help us take advantage of in-vehicle, infrastructure-based, and public data sets to inform and improve our research.
You will collaborate with vehicle, transportation and wireless communication experts, global Company researchers, and academic partners on research projects and real-world trials.
Come work with us to make the vehicles and the transportation system of the future safer, more convenient, and more connected!
- Work with research team to identify the data requirements, available data source (internal and external such as geo-location specific or social media) and expected outcomes in Connected and Automated Vehicle (CAV) research and experiments
- Recommend and support data collection, integration and retention requirements by assess the effectiveness and accuracy of data source and data gathering techniques
- Apply advanced statistical and predictive modeling techniques to validate the findings, build, maintain and improve as iterative approach
- Coordinate with various teams to implement models
- Develop experimental design approaches to validate findings or test hypotheses
- Identify opportunities such as discovering new patterns form large data sets, and find solutions hidden in large data sets to improve the features/applications and find new features/applications
- Define the validity of data such as how the information is meaningful, and what other information it is related to
- Ensure the data is in compliance with the regulatory and security policies in place
- Develop usage and access control policies and systems in collaboration with other data related departments
- Provide ongoing tracking and monitoring of performance of the statistical models, recommends ongoing improvements to methods and algorithms that lead to findings, including new information
- Lead the design and deployment of enhancements and fixes to systems as needed
- Present and depict the rationale of the findings in easy to understand terms to the research team and to the management
- Educate the team (CAV research and IT department) on new approaches, such as testing hypotheses and statistical validation of results
Must Have Skillsets:
- 2 years experience of hands on Data Collection and Implementation
- Demonstrated experience solving loosely defined problems by leveraging pattern detection over potentially large data sets
- 2+ years’ after school practical experience with data storage and analysis tools such as Sql, Hadoop or other big data frameworks
- 2+ years’ statistical modeling using tools such as Python, MATLAB, R, and/or SAS
- Experience creating and using advanced machine learning algorithms and statistics.
- Experience in statistical techniques and concepts (Properties of distributions, statistical tests and proper usage, etc.) and applying these to applications
- Master’s or PhD degree (Preferred) in any one of the following disciplines (Machine Learning, Statistics, Applied Mathematics, Computer science or another quantitative field)
- Experience with Consumer Behavior, Vehicle User, Transportation User, Behavior User, etc.
- Experience with intelligent Transportation Systems (ITS) or vehicular data
- Familiarity with either telematics, wireless networking, or V2V V2I communications protocols (examples: 3G, 4G LTE, 5G, UDP, IEEE802.11, CAN, V2V, V2I, V2X …)
- Experience programming within Unix-based operating systems, such as Linux
- Programming in Python
- Experience with any of these: AWS, Azure, Big Data, Machine Learning, Data Science, Time Series, Data Visualization
- Have a passion to create and try new ideas
- Effective communication skills, both verbal and written
- Demonstrated ability to be productive independently or in a small team environment
- Eager to quickly learn by searching, reading, by example and trial & error
- Comfortable working in a multicultural environment
- Accept some travel
- Accept long hours on occasion
Location: Southfield, Michigan
Type: Contract or Fulltime (relocation assistance is available)