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The Data Scientist is responsible for collecting, cleaning, and managing data to meet the company’s purpose and improve our computer vision models for our perception(computer vision) software. Utilize analytical, statistical, and programming skills to collect, analyze, and interpret large data sets. Some of their responsibilities include updating current software systems, making improvement suggestions, collaborating with analysts and designers, testing applications, documenting procedures, writing training manuals, and ensuring projects are completed on time and within budgetJob Description.

Let’s Make Our Roads Safer

  • Experience: 2 to 5 years plus in data science, software design, and development. Have a proven track record developing models—preferred experiences in camera and LiDAR model development. 
  • Education: BS/MS/Ph.D. in Robotics in Artificial Intelligence, Statistics, Information Systems, Software Engineering, Computer Science, Electrical Engineering, Applied Math, Physics, or the equivalent in experience and evidence of exceptional ability. A Ph.D. in developing deep learning and machine learning models is preferred.
  • Location: Scottsdale, AZ, or remote
  • Department: Technology and Product Development
  • Coding Languages: Must have a minimum of three years in C++ and/or Python
  • Technical Skills: general knowledge and development in machine learning and deep learning. A drive to learn and master new technologies and techniques.
  • Sensor Technology: A plus if you have experience with LiDAR, camera, RADAR, and sensor fusion.
Sensagrate is developing a smart city and smart infrastructure platform that provides real-time data to support intelligent decision-making for smart city use cases. The platform is a computer vision perception AI software and reporting called SensaVision developed from deep learning algorithms for cameras (2D) and LIDAR (3D) data. We use the 2D and 3D visual data to merge into a process called sensor fusion. The software detects, classifies, and tracks motorized and non-motorized objects in real-time and aggregates the data for analytics and reporting. We target a 95% object detection accuracy rating as our algorithms continue to learn. Smart city and infrastructure applications can improve some key quality-of-life indicators by 10% to 30%. Review our fact sheet.