Data Scientist, Repair Order (RO) Duration Analytics

Ford Motor Company · Dearborn, Michigan, United States · $100K–$193K/yr

Motor Vehicle Manufacturing · 10,001+ employees

6 h ago

Mid (2-5 yrs) Full-time Visa sponsorship United States

About the role

The Data Scientist will develop and deploy analytical frameworks and models to optimize repair order duration and improve service efficiency. They will analyze vast datasets to provide actionable insights and support evidence-based decision-making for the Ford Customer Service Division.

What they look for

Data science Statistical analysis Optimization Machine learning Deep learning Forecasting models Python SQL Generative AI Big data manipulation Feature engineering Econometrics Google Cloud Platform BigQuery Vertex AI LLM

Requirements

Candidates must have a Master's degree in a quantitative field and at least 3 years of experience in big data, statistical analysis, and machine learning. Proficiency in Python and SQL is required, along with strong problem-solving skills and the ability to navigate ambiguous environments.

Benefits

Medical coverage Dental coverage Vision coverage Prescription drug coverage Flexible family care days Paid parental leave New parent ramp-up programs Subsidized back-up childcare Adoption and surrogacy expense reimbursement Fertility treatments Vehicle discount program Tuition assistance Employee resource groups Paid time off for community service Paid holidays

Full description

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.

At Ford Motor Company, we believe freedom of movement drives human progress. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career and help us define tomorrow’s transportation.

We are trusted advisers enabling Ford to see our business, know our customers and act in a meaningful way. We drive evidence-based decision making by providing timely, actionable and forward-looking insights to our One Ford business partners. We seek to provide the thought leadership essential to achieving Ford’s strategic objectives. We translate insight into action by driving toward robust points of view, timely decisions and responsible allocation of enterprise resources.