AI/ML Technical Expert - Customer Usage Data Scientist

We are seeking a highly accomplished, cross-disciplinary Senior Data & AI Solutions Architect to lead the convergence of big data telemetry engineering, platform-native agentic AI development, and automotive quality intelligence. This role bridges enterprise data infrastructure with conversational and autonomous intelligence to transform large-scale, multi-sensor connected vehicle data into proactive engineering and business solutions.

The ideal candidate will architect and optimize end-to-end ETL/ELT pipelines across Databricks and Palantir Foundry; develop specialized conversational and logic agents using Databricks Genie AI, Palantir AIP Analyst, and Palantir AIP Logic; and correlate real-world customer usage profiles and Diagnostic Trouble Code (DTC) events with warranty performance, issue management workflows, predictive analytics, and physical vehicle test fleet scheduling.

Key Responsibilities:

Dual-Platform Pipeline Architecture & Big Data Performance Optimization

Architect, refactor, and maintain high-throughput ETL/ELT pipelines using PySpark across Databricks and Palantir Foundry Code Workbooks. Modernize data processing procedures, optimize partitioning strategies and compute resource allocation, and eliminate runtime bottlenecks when transforming massive, multi-sensor JSON telemetry streams into scalable, query-ready analytical data products.

Platform-Native Agentic AI & Conversational Intelligence

Design, configure, deploy, and operationalize enterprise AI agents and natural-language analytical workflows across Databricks and Palantir platforms.

• Databricks Genie AI: Construct and curate Genie Spaces, configure semantic metadata over Unity Catalog tables and views, and develop benchmark questions and instructions that enable engineers and business leaders to query complex fleet telemetry, warranty, and operational metrics through natural language.

• Palantir AIP Ecosystem: Build and orchestrate intelligent agentic applications using Palantir AIP Analyst, AIP Logic, and Palantir Workshop, binding LLM-driven reasoning to Foundry Ontology Object Types, relationships, and permissioned Actions for automated issue summarization, root-cause investigation, interactive analytics, and operational workflow execution.

Customer Usage, DTC Events & Warranty Intelligence

Ingest, transform, and model high-frequency connected vehicle telemetry to quantify real-world customer driving behaviors, environmental stress profiles, vehicle usage patterns, and duty cycles. Correlate customer usage characteristics and DTC snapshot events with warranty claims and vehicle population data to identify emerging quality signals, accelerate issue management and root-cause investigation, and support warranty cost reduction.

Predictive Modeling & Statistical Reliability Analytics

Develop predictive and statistical models to identify emerging warranty risks, quantify failure behavior, and forecast future vehicle quality performance. Apply reliability modeling, machine learning, and data-driven validation techniques to translate historical and real-world vehicle data into actionable engineering intelligence.

Vehicle Validation & Test Fleet Scheduling

Apply customer usage analytics, warranty intelligence, and operational AI workflows to optimize physical vehicle validation strategies and prototype test fleet operations. Translate real-world duty cycles and failure patterns into data-driven test priorities, vehicle allocation strategies, and validation schedules for full-size vehicle platforms.

Full-Stack Analytical Applications & Business Intelligence

Build end-to-end operational applications, decision-support systems, and executive dashboards using Palantir Workshop, Palantir Slate, Power BI, and Tableau. Integrate conversational AI capabilities directly into analytical applications to enable interactive exploration, automated insights, and decision support.

Statistical Rigor, Data Quality & Governance

Establish data validation, analytical quality, and governance frameworks across hybrid enterprise environments. Combine rigorous statistical methodologies with distributed data engineering practices and enterprise governance capabilities across Databricks Unity Catalog and Palantir Foundry Ontology.