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Data Scientist, Repair Order; RO Analytics

Job in Dearborn, Wayne County, Michigan, 48120, USA
Listing for: Ford Motor Company
Full Time position
Listed on 2026-07-14
Job specializations:
  • IT/Tech
    Data Analyst, AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 99600 - 192900 USD Yearly USD 99600.00 192900.00 YEAR
Job Description & How to Apply Below
Position: Data Scientist, Repair Order (RO) Duration Analytics

We made history and now we work to transform the future – for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.

Do you believe data tells the real story? We do! Redefining mobility requires quality data, metrics and analytics, as well as insightful interpreters and analysts. That's where Global Data Insight & Analytics makes an impact. We advise leadership on business conditions, customer needs and the competitive landscape. With our support, key decision makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision making.

FCSA (Ford Customer Service Analytics) team, part of Sales and Services Data and Analytics (SSDA) department in Ford’s Global Data, Insight and Analytics (GDI&A) organization, is looking for a highly skilled Data Scientist. This role will be a member of the Repair Order (RO) Duration Analytics team, supporting all stages of RO duration analysis from problem formulation, model/analytical framework development, and evaluation, to model deployment to help Ford achieve RO duration optimization and efficiency objectives.

The RO Duration Analytics team applies advanced quantitative methods, econometrics, and AI/ML/LLM techniques to derive insights and solve a wide variety of challenging problems in various areas of Ford Customer Service Division. This includes: RO duration forecasting, RO duration monitoring/trend study, RO duration root causes, repair process optimization and analytical support, vehicle off-road/uptime, and early quality detection… through analyzing vast amounts of data.

This role will be instrumental in supporting business objectives and transformation through data-driven decision-making.

  • Model Development & Forecasting:
    Design, build, scale, and maintain RO duration forecasting and predictive models, leveraging operational and market inputs such as repair types, fuel types, customer segments, product quality, service parts availability, dealer capacity, and macroeconomic indicators.
  • Data Quality & Governance:
    Establish and ensure high standards of data quality, model governance, and validation testing throughout the entire analytics development lifecycle.
  • Root-Cause & Deep-Dive Analysis:
    Lead deep‑dive and root‑cause analyses on vehicles with extended repair times to identify early indicators of anomalies, isolate inefficiencies, and uncover actionable insights to reduce RO duration.
  • Agile Exploratory Studies:
    Execute high‑impact, agile exploratory analyses to address critical, time‑sensitive business questions by mining and transforming massive, high‑dimensional structured and unstructured datasets.
  • GenAI Innovation:
    Leverage LLMs and agentic workflows to extract intelligence from data and automate analytical workflows.
  • Model Deployment & MLOps:
    Partner cross‑functionally with data engineers, software engineers, and architects to build robust model pipelines, validate outputs, and deploy scalable ML/LLM models into production GCP environments.
  • Technical Translation & Communication:
    Independently translate complex quantitative methodologies and modeling outputs into clear, compelling, and actionable insights for non‑technical business partners and executive leadership.
Minimum Qualifications
  • Master’s Degree in Data Science, Statistics, Economics, Engineering, Physics, or related quantitative field or a combination of education and equivalent work experience.
  • 3+ years of experience in big data manipulation, statistical analysis, and optimization, including hands‑on experience training, evaluating, and fine‑tuning ML, deep learning, and forecasting models.
  • 3+ years of experience processing and engineering large, high‑dimensional structured and unstructured datasets (including data cleaning, preprocessing, and feature engineering).
  • 3+ years of proficiency in Python and SQL (writing clean, scalable code) along with experience leveraging modern generative AI environments (e.g., Open Code) to accelerate development and ensure quality.
  • S…
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