ABOUT EXPONENT

Exponent is the only premium engineering and scientific consulting firm with the depth and breadth of expertise to solve our clients’ most profoundly unique, unprecedented, and urgent challenges.
Our vision is to engage multidisciplinary teams of science, engineering, and regulatory experts to empower clients with solutions that create a safer, healthier, more sustainable world. For over five decades, we’ve connected the lessons of past failures with tomorrow’s solutions to advise clients as they innovate technologically complex products and processes, ensure the safety and health of their users, and address the challenges of sustainability.
Join our team of experts with degrees from top programs at over 500 universities and extensive experience spanning a variety of industries. At Exponent, you’ll contribute to the diverse pool of ideas, talents, backgrounds, and experiences that drives our collaborative teamwork and breakthrough insights. Plus, we help you grow your career through mentoring, sponsorship, and a culture of learning. Thanks for your interest in joining our team!

OUR OPPORTUNITY

We are currently seeking a Machine Learning Data Acquisition Scientist (Ph.D.) for our Data Sciences Practice in our Menlo Park, CA office. In this role, you will work as part of a team to plan and execute global data collection efforts, utilize and improve next-generation products, and optimize internal and external programs to support clients in the consumer electronic industry.

YOU WILL HAVE THE FOLLOWING SKILLS AND QUALIFICATIONS

• 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)
• Ability to take an ambiguous question, use data to draw insights, and convey the results to a wide range of audiences
• Demonstrated experience collecting data with human subjects
• Interest and ability to work onsite to scale and manage large-scale data collection operations
• 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
• 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

YOU MAY ALSO HAVE THE FOLLOWING SKILLS AND QUALIFICATIONS (OPTIONAL BUT BENEFICIAL):

• 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
  Applicants are encouraged to submit a CV (Curriculum Vitae) with publications (feel free to include publications that are in review or pending) [not restricted to 1 page].

• 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