Data Scientist

Requirements

• M.Sc. required, Ph.D. a plus in Computer Science, Statistics, Math, Physics or similarly quantitative-heavy field
• At least 5+ years of related industry experience
• Expertise in a wide range of machine learning techniques, including deep learning, reinforcement learning, and statistical modeling
• Experience working with large-scale datasets with solid understanding of data processing, feature engineering, and data visualization techniques
• Practical experience with data science and machine learning methods, common cloud-based data analysis tools and frameworks (Spark, SQL, Pandas, Python, R, AWS, GCP, PySpark, scikit-learn, OpenCV, etc)
• Embraces scientifically rigorous mindset to algorithm development based on well designed experiments using real-world data to evaluate, validate and iterate
• Strong communication and presentation skills, with the ability to effectively convey technical information to internal and external audiences
• Leadership experience is a plus
• Start-up experience a plus

• We are seeking a highly experienced and strategic Senior Staff Data Scientist to lead high-impact initiatives that drive measurable business value
• In this role, you will be a key driver of data innovation, mentor other data scientists, and collaborate cross-functionally with Product, Engineering, and Business leaders to inform decision-making and product development
• You will be responsible for designing and deploying cutting-edge machine learning models that analyze vision & sensor data, leading analytical initiatives, and shaping the long-term data science strategy
• Your work will directly impact driver behavior, vehicle performance, and operational safety across tens of thousands of commercial fleets
• Design, build and deploy solutions to challenging problems leveraging access to vast real-world data
• Create large datasets to discover insights helpful in developing new approaches and algorithms to advance the state of the art in transportation safety
• Collaborate with multiple teams (Product, Perception, Device Engineering, Customer Success) to identify and clarify business or product questions, to answer and provide feedback, and to translate and refine business questions into tractable analysis, evaluation metrics or mathematical models