Your Role
Data Analytics Engineer
Roles and Responsibilities
Vehicle Data Mining & Analytics
•Lead DM&A Team for AWS/Azure/Other HPCs
•Perform vehicle data mining and exploratory analysis using Python and data-science tools
•Support event extraction and triage for customer-reported and internal issues
•Analyze vehicle signals and logs (CAN, Ethernet) to identify anomalies and performance concerns
•Apply structured problem-solving techniques to support root-cause analysis
AI / Machine Learning Support
•Support AI/ML validation workflows for ADAS features, including: dataset exploration and quality assessment, feature analysis and labeling support, and review of basic ML performance metrics
•Assist in identifying data issues impacting ML model behavior (e.g., noise, missing signals, data drift)
•Build foundational understanding of how ML models interact with embedded ADAS systems
Embedded-Level Debugging & System Understanding
•Support embedded-level triage activities, like ECU log analysis, vehicle communication trace interpretation and signal-to-algorithm correlation
•Assist in debugging issues that span vehicle sensors, embedded software, and analytics outputs
•Learn ADAS system architecture and data flow from sensor → ECU → analytics → validation
Vehicle Testing & Data Collection
•Participate in hands-on vehicle testing and data collection under guidance of senior engineers
•Support vehicle instrumentation, logging setup, and data validation
•Help ensure collected data meets analysis and validation requirements
Collaboration & Process Adherence
•Work closely with the algorithm development team, systems and validation engineers, and project and engineering managers
•Follow established ADAS V-cycle development, validation, and documentation processes
•Contribute to continuous improvement of data analysis tools and workflows
Your Background
•Bachelor's or Master's degree in a relevant field, such as: Data Science, Computer Engineering, Electrical / Embedded Systems Engineering, or Automotive or Systems Engineering
•2+ years experience and proficient in Python, vehicle communication protocols – CAN, Ethernet, data science tools with analytics
•Familiar with MATLAB, machine learning algorithms, DBQL/SQL, Linux
•Hands-on experience with vehicle instrumentation
•Proficient in structured problem solving
•Clear understanding of embedded systems fundamentals (ECUs, signals, logs)
Nice to Haves
•Academic or project experience in AI / Machine Learning, ADAS or autonomous driving systems, and vehicle data analytics
•Exposure to vehicle communication protocols (CAN, Ethernet), embedded debugging (logs, traces, signal analysis), and MATLAB, basic C/C++, or signal processing
•Familiarity with automotive tools such as CANalyzer or CANoe, SIL (Software in the Loop) or simulation environments, Agile / Scrum development practices
Traits We Seek
•Curious and analytical mindset with strong problem-solving skills
•Hands-on learner who enjoys working with real systems and data
•Structured and detail-oriented approach to analysis
•Collaborative team player open to feedback and mentorship
•Resilient and growth-focused, viewing challenges as learning opportunities
Your Benefits
•Higher Education Opportunities (Udacity, Udemy, Coursera available for continuous growth and development)
•Life and accident insurance
•Sodexo cards for food and beverages
•Well Being Program that includes regular workshops and networking events
•EAP Employee Assistance
•Access to fitness clubs (T&C apply)
•Creche facility for working parents
