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As a Senior Prognostics Data Engineer- Low Voltage within LVI, you'll design, validate, and deploy production-ready prognostic algorithms that predict and prevent low voltage failures. Your work will detect parasitic drains, assess electrical system health, and enable timely service and customer interventions—reducing walk‑home events and unnecessary warranty expense. You’ll collaborate closely with systems, diagnostics, software, calibration, quality, and service teams to turn vehicle data into scalable, field‑proven prognostic algorithms. This is an assignment where creativity, analytical thinking, deep customer insight, and exceptional collaboration are crucial and celebrated!
Job Responsibility
Design, develop, and deploy prognostic algorithms for low voltage components and parasitic drain detection (lithium ion batteries)
Model low voltage system behavior and failure modes
monitor degradation trends over vehicle life
Pilot and validate prognostic features in development and test fleets, then support production rollout
Partner with diagnostics, service engineering, vehicle health management, analytics, and aftersales to ensure prognostics outputs are actionable and integrated into tools and notifications
Analyze field data to evaluate alert effectiveness and tune thresholds and calibrations
Collaborate with architecture and safety teams to ensure prognostic strategies meet system safety goals, ASIL targets, and regulatory requirements
Develop roadmaps and strategy for low voltage prognostics across architectures, programs, and model years
Apply statistical analysis, anomaly detection, clustering, and signal processing to uncover new patterns in vehicle telemetry data
Requirements
Bachelor's degree in Engineering or Computer Science
Minimum 5+ years of engineering experience related to automotive prognostics, diagnostics, embedded controls, or data analytics
Strong experience in Python, major machine learning frameworks, and SQL
Experience with data visualization and analytics platforms (i.e. PowerBI, Databricks Apps, Azure Apps)
Exceptional analytical and problem-solving skills, with a track record of data-driven decision making
Demonstrated ability to turn ambiguous problems into clear requirements, value proposition, models, and technical solutions
Strong communication and collaboration skills, with experience working across cross-functional teams
Nice to have
Master's degree (or higher) in Engineering or Computer Science
Experience developing prognostics for low voltage systems, energy storage, power conversion, or load management
Experience with degradation modeling and long‑term health monitoring
Understanding of vehicle manufacturing, service, and warranty processes—including how prognostic content flows into service tools and customer‑facing messages
Familiarity with functional safety (ISO 26262, ASIL) and their impact on system and software design
Experience with advanced analytics techniques, LLMs, or AI‑enabled tooling applied to vehicle health, prognostics, diagnostics, or service insights