Exponent is seeking a Machine Learning Data Acquisition Scientist (Ph.D.) to support clients in the consumer electronic industry by planning and executing global data collection efforts, utilizing and improving next-generation products, and optimizing internal and external programs.
Requirements
- Ph.D. in a relevant science or engineering field, such as Cognitive Science, Human-Computer Interaction, Electrical Engineering, or Robotics. A wide range of disciplines may also be considered (such as Kinesiology, Applied Physics, Statistics, Industrial Engineering, Mechanical Engineering, or Applied Mathematics)
- Demonstrated experience collecting data with human subjects
- Demonstrated expertise in one or more of the following areas: Advanced sensing technology, Networking data analysis and visualization, Experience with large data sets, Prototyping, Operations optimization, Machine learning data set design or optimization, Dynamic system modeling and control
- Experience with qualitative data collection and analysis methods
- Experience synthesizing information across a variety of sources (such as academic literature, government reports, journalistic articles, etc.) across human-centered subjects
- Theoretical knowledge of human-AI interaction, social networks, and/or other sociotechnical ecosystems
Responsibilities
- Supporting a range of consulting activities related to large-scale local and global programs to build custom datasets for machine learning algorithms, including protocol development and documentation, participant moderation, data collection, data management, and analysis
- Providing operational support for prototype hardware and software systems, including system validation and troubleshooting
- Actively solving technical and logistical problems in a fast-paced environment
- Creating and leading ad hoc interdisciplinary teams comprised of consultants from Data Sciences, Human Factors, Health Sciences, and Engineering Sciences
- Developing data analysis and visualization tools related to project management, demographics, and human-centered data
Other
- Ability to take an ambiguous question, use data to draw insights, and convey the results to a wide range of audiences
- Interest and ability to work onsite to scale and manage large-scale data collection operations
- The desire to work with a diverse set of clients and engage in work outside of the traditional data science field
- Strong practical engineering ability combined with leadership and project management skills
- Excellent verbal and written communication skills
- Ability to work independently and in multidisciplinary teams
- Up to 25% travel to a variety of domestic and global locations to support project work
