Data Scientist – Conversational AI

Ford Motor Company

Data Scientist in Ford’s Digital Cabin team shaping data strategy for next-gen AI Digital Assistant. Leverages NLP and machine learning to enhance user experience and vehicle functions.

Posted 7/23/2026full-timeDearborn • Missouri • 🇺🇸 United StatesSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Natural Language Processing, Applied Machine Learning, and Data Analytics, with a strong focus on building advanced visualizations and conducting A/B testing to drive product insights. Proficient in SQL and Google Cloud Platform, capable of integrating and structuring complex datasets while ensuring data privacy standards.

Highest-signal resume keywords

Natural Language ProcessingApplied Machine LearningExpert-Level SQLGoogle Cloud PlatformAdvanced Visualization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Natural Language ProcessingMachine LearningSQLPythonRData AnalyticsA/B TestingText AnalyticsClusteringData Integration

Soft Skills

Strategic Problem SolvingCollaboration

Tools & Technologies

Google Cloud PlatformLookerPowerBIGitGitHub

Industry Keywords

Data ScienceProduct AnalyticsSentiment AnalysisData PrivacyPII Handling

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

NLP & Utterance Analysis: 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.
AI Response Evaluation & Experimentation: 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.
Data Integration & Sanitization: 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.
Problem Framing & Metric Definition: Act as a strategic partner to Product Managers. Challenge assumptions and define core conversational metrics (e.g., task success rates, user engagement, support deflection).
Advanced Visualization & Self-Service: 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.
Bridge the Mobile-to-IVI Gap: Act as the analytical bridge as our digital assistant expands from the Ford app into the vehicle, standardizing mobile data against our emerging in-vehicle data contracts.

Requirements

What you’ll need

Education: A Master's Degree in a quantitative, technical, or related field (e.g., Data Science, Computer Science, Statistics).
Experience: 7+ years of experience in Data Science, Product Analytics, or Applied Machine Learning.
"Full-Stack" Capability: Demonstrated ability to act as a bridge between Data Science, Engineering, and Product—taking raw telemetry, applying statistical/ML models, and transforming it into business insights without relying on a central data team for every step.
Applied ML & LLM Analytics: Proficiency in Python or R with hands-on experience in text analytics, clustering, and categorization. Familiarity with LLM evaluation techniques (e.g., prompt effectiveness, hallucination tracking, human-in-the-loop feedback).
Expert-Level SQL & GCP: Highly proficient in writing complex, optimized SQL (Window Functions, CTEs, handling JSON/Nested Data) within Google Cloud Platform (BigQuery) to structure datasets independently.
Advanced Visualization: Deep expertise in building scalable business intelligence solutions, semantic layers, and executive-facing dashboards in Looker and PowerBI.
Experimentation: Strong grasp of statistics and experience designing and measuring A/B tests in a product environment.
Analytics as Code: Experience with version control (e.g., Git, GitHub) and working in environments where analytics changes go through a formal peer-review process.
Strategic Problem Solving: Comfortable navigating complex, multi-source data environments. You view data integration as a puzzle to be solved and a strategic enabler for the business.

Benefits

Comp & perks

Immediate medical, dental, vision and prescription drug coverage
Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
Paid time off and the option to purchase additional vacation time.