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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - Conversational AI - **Company:** Ford Motor Company - **Location:** Dearborn, MI, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Data Analysis, BigQuery, Cluster Analysis, Data Integration, Executive Information Systems, Github, JSON, Python (Programming Language), Machine Learning, Natural Language Processing, Performance Tuning, Software Product Management, Raw Data, Power BI, Sentiment Analysis, SQL Databases, Usage Analysis, Google Cloud, Chatbots, Large Language Models, Data Build Tool (dbt), Data Strategy, Git, Data Layers, Information Technology, Text Analysis, Looker Analytics, Software Version Control, Mobile Data - **Published:** July 24, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=dcb602b7f6f09bdb ## About the Role * 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. Primary Technical Skills * 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. Even better, you may have... * Behavioral Analytics: Experience using platforms like Amplitude to analyze user funnels, retention curves, and cohort behavior. * Data Modeling: Experience with dbt (Data Build Tool) or similar frameworks for transforming data in the warehouse. ## Description You will join the Digital Cabin organization as the dedicated Data Scientist for our next-generation AI Digital Assistant. This AI-driven feature is currently active on mobile platforms and is rapidly expanding into our In-Vehicle Infotainment (IVI) systems to 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. We are looking for a strategic, "full-stack" Data Scientist who leans heavily into Product Analytics. You must be willing to roll up your sleeves to structure raw data and build executive dashboards, while also deploying applied machine learning techniques to categorize user utterances, evaluate AI performance, and drive behavioral insights. What you'll do... * 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. ## Related Videos - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [How software is steering vehicle technology](https://www.wearedevelopers.com/magazine/515-how-software-is-steering-vehicle-technology) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [13 AI Tools You Have to Try](https://www.wearedevelopers.com/magazine/219-13-ai-tools-you-have-to-try)