VOC Analytics Leader: GenAI, NLP & Predictive Insights

Hyundai Motor Company; Fountain Valley (CA); On-site; USD 114,800 - 164,000; Full time

Benefits offered by this job

Vehicle lease

Holiday pay

Health insurance

401(k)

Job summary

Hyundai Motor Company in the United States is seeking a senior leader for advanced analytics to drive predictive, prescriptive, and root-cause insights across VOC, product quality, and customer care data. You will apply statistical modeling, machine learning, and GenAI techniques to identify risks, optimize operations, and improve customer satisfaction.

You will define the analytics roadmap, lead analytics teams, collaborate with data engineering, and present findings to executives.

Qualifications

• Bachelor's degree in a quantitative field is required.
• Eight or more years in data analytics, BI, or data science.
• At least three years leading analytics teams.
• Experience in automotive, customer care, VOC, or product quality analytics preferred.
• Advanced analytics: Python, SQL; NLP/GenAI familiarity a plus.

Responsibilities

• Lead advanced analytics initiatives across VOC, product quality, and customer care data.
• Define and execute the analytics roadmap and identify high-impact opportunities.
• Develop predictive models for warranty forecasting, churn, and case escalation risk.
• Apply NLP and GenAI to unstructured VOC data and conduct experiments.
• Present findings to senior leadership and guide data scientists and analysts.

Skills

Python

SQL

Azure AI

GenAI APIs

NLP

Education

Bachelor's degree

Tools

OpenAI/Claude APIs

Azure AI

Job description

Hyundai Motor Company in the United States is seeking a senior leader for advanced analytics to drive predictive, prescriptive, and root-cause insights across VOC, product quality, and customer care data. You will apply statistical modeling, machine learning, and GenAI techniques to identify risks, optimize operations, and improve customer satisfaction.

You will define the analytics roadmap, lead analytics teams, collaborate with data engineering, and present findings to executives.