Product Manager - AI

You will join the Digital Cabin organization as the dedicated Data Scientist for our next-generation AI Digital Assistant. This AI-driven feature is live on mobile and rapidly expanding into our In-Vehicle Infotainment (IVI) systems to answer questions, execute tasks, provide vehicle reports, and enhance the driving experience.

This role offers a unique opportunity to shape the data strategy for a high-priority AI product from the ground up. As a hands-on individual contributor, you'll build the analytics foundation and dashboards the product team relies on, and lead the evaluation work that answers the harder questions: Is the assistant giving good answers and completing tasks successfully? How do we know our measurements are right? And what is it worth to the business?

What you'll do…

• AI Response & Task Evaluation: Design methodologies to evaluate both informational responses (accuracy, grounding, helpfulness) and task completion (did the assistant understand the request, take the right action, and finish the job, including across multi-turn conversations). Build ground-truth evaluation sets from real conversations, keep development and held-out test sets separate, and run regression checks on every prompt and model update.

• Validate the Evaluation: Calibrate automated scoring, including LLM-as-judge, against human review, and confirm offline scores match real user behavior such as retries and abandoned sessions. When they disagree, fix the evaluation rather than defend the score.

• NLP & Utterance Analysis: Cluster and categorize raw user utterances to build an intent taxonomy from what users actually say. Perform sentiment and failure analysis to surface actionable product insights.

• Business Impact: Analyze how the assistant relates to outcomes such as warranty claims, support contacts, and connectivity subscription conversion, using methods that account for selection bias so leadership gets credible estimates, not misleading correlations.

• Data Integration & Sanitization: Work directly in Google Cloud Platform (GCP) to join and structure mobile, vehicle, customer support, warranty, and subscription data into robust analytical datasets, ensuring strict adherence to data privacy and PII handling standards.

• Problem Framing & Metric Definition: Act as a strategic partner to Product Managers. Challenge assumptions and define core conversational metrics (e.g., task success rate, containment, support deflection).

• Dashboards & Self-Service: Build and maintain narrative-driven dashboards in Looker and/or Power BI that empower the product team to answer their own day-to-day questions.

• Bridge the Mobile-to-IVI Gap: Act as the analytical bridge as the assistant expands from the Ford app into the vehicle, standardizing mobile data against emerging in-vehicle data contracts and partnering with instrumentation teams on what gets logged.