Data Scientist - Conversational AI

Ford Ford · Auto · Dearborn, MI +1 · Ford Next Businesses

Data Scientist for Ford's next-generation AI Digital Assistant, focusing on Product Analytics and Applied ML. The role involves NLP for utterance analysis, evaluating AI response quality, data integration on GCP, defining conversational metrics, and building dashboards. The goal is to enhance the driving experience by expanding the AI assistant from mobile to in-vehicle systems.

What you'd actually do

  1. Leverage Natural Language Processing (NLP) and machine learning to categorize and cluster raw user utterances. Perform sentiment analysis on unstructured text logs to extract actionable product insights.
  2. Design methodologies to evaluate the helpfulness, accuracy, and relevance of the AI’s responses. Design and analyze A/B tests to measure the impact of prompt adjustments, model updates, and new feature rollouts.
  3. Dive directly into Google Cloud Platform (GCP) to cleanly join and structure mobile, customer support, and vehicle data into robust "Analytical Sandboxes," ensuring strict adherence to data privacy and PII handling standards.
  4. Act as a strategic partner to Product Managers. Challenge assumptions and define core conversational metrics (e.g., task success rates, user engagement, support deflection).
  5. Design, build, and maintain highly intuitive, narrative-driven dashboards using Looker and PowerBI to empower the product team to answer their own day-to-day questions.

Skills

Required

  • Python or R
  • Text analytics
  • Clustering
  • Categorization
  • LLM evaluation techniques
  • Prompt effectiveness
  • Hallucination tracking
  • Human-in-the-loop feedback
  • SQL
  • Google Cloud Platform (GCP)
  • BigQuery
  • Looker
  • PowerBI
  • A/B testing
  • Git
  • GitHub
  • Master's Degree in a quantitative, technical, or related field

Nice to have

  • Amplitude
  • dbt

What the JD emphasized

  • 7+ years of experience in Data Science, Product Analytics, or Applied Machine Learning
  • Demonstrated ability to act as a bridge between Data Science, Engineering, and Product
  • Proficiency in Python or R with hands-on experience in text analytics, clustering, and categorization
  • Familiarity with LLM evaluation techniques
  • Expert-Level SQL & GCP
  • Highly proficient in writing complex, optimized SQL
  • Deep expertise in building scalable business intelligence solutions, semantic layers, and executive-facing dashboards in Looker and PowerBI
  • Strong grasp of statistics and experience designing and measuring A/B tests in a product environment

Other signals

  • AI Digital Assistant
  • Product Analytics
  • Applied Machine Learning
  • LLM Evaluation