Data and AI Lead

Responsibilities

• Diagnose Data Engineering & Architecture
• Define and execute the Data science, machine Learning and AI-powered diagnostics roadmap for DTC/DID evolution
• Transition from rule-based diagnostics → predictive and prescriptive diagnostics
• Drive data-centric architecture for vehicle health monitoring and diagnostics intelligence
• Collaborate with OEM stakeholders to embed AI into vehicle lifecycle (in-vehicle + cloud)

Data Science & AI Leadership

• Lead development of ML/AI models for:
• Fault detection and classification
• Root cause analysis
• Remaining Useful Life (RUL) prediction
• Anomaly detection in telemetry and ECU signals
• Apply advanced analytics on:
• Time-series vehicle data
• CAN/LIN/Ethernet communication data
• Sensor fusion data streams
• Establish model lifecycle management (MLOps) for continuous learning and deployment

Diagnostics Strategy & Engineering Enablement

• Support definition and continuous improvement of vehicle diagnostics strategy for ICE, Hybrid, and EV platforms
• Collaborate with system and software teams to:
• Improve onboard diagnostics (OBD) logic
• Enhance remote and OTA diagnostics capabilities
• Enable predictive diagnostics using advanced analytics/ML
• Translate product and engineering requirements into data-driven diagnostics solutions
• Platform & Architecture
• Define scalable data architectures for diagnostics:
• Edge (in-vehicle) + Cloud (off-board analytics)
• Work with engineering teams to build:
• Diagnostic data lakes
• Real-time streaming pipelines
• Ensure integration with:
• Vehicle telemetry platforms
• Digital twin ecosystems

Tooling, Automation & Advanced Analytics

• Develop and deploy tools for:
• Diagnostics data mining and automation
• Fault pattern recognition
• Data-driven decision-making
• Leverage AI/ML techniques for predictive failure detection
• Enable self-service data analytics platforms for engineering users

Requirements

• Required Skills:
• Bachelor’s or master’s degree in Computer Science / Data Engineering
• 5–10 years of experience in automotive, data engineering, or diagnostics domain
• Strong technical expertise in:
• Python
• SQL
• Data platforms (Spark, Databricks, or similar)
• Cloud ecosystems (Azure preferred )
• Experience in handling large-scale automotive datasets
• Strong analytical and problem-solving skills
• Ability to convert complex data into engineering insights
• Excellent stakeholder communication and collaboration
• Understanding of automotive system architecture
• Agile mindset with a focus on innovation and continuous improvement

Preferred Skills

• Hands-on experience with:
• Data Science and AI and ML
• Masters in data science, AI and ML

Compensation and Benefits

• Competitive pay
• Geo Blue PPO and HSA plan
• MetLife – Dental and Vision plan
• Healthcare and Dependent care flexible spending account(FSA)
• 401k with employer match
• Company-paid Basic Life and Long-term disability insurance
• Voluntary benefits include Critical Illness, Hospital indemnity, accident insurance, theft, and legal service
• Employee Assistance Program
• Paid Holidays
• Employee discounts and perks
• Gym benefit