Data and AI Lead

Job Description

Responsibilities:

Diagnostics Data Engineering & Architecture

Diagnostics Strategy & Transformation

• 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:

Along with competitive pay, as a full-time KPIT employee, you are eligible for the following benefits:

• 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.