We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world -- together. At Ford, we’re all a part of something bigger than ourselves. Are you ready to change the way the world moves?

The Ford Motor Credit Company team helps put people behind the wheels of great Ford and Lincoln vehicles. By partnering with dealerships, we provide financing, personalized service and professional expertise to thousands of dealers and millions of customers in over one hundred countries around the world.

In this position...

We are seeking a highly motivated and quantitatively skilled Credit Loss Model Analyst to join our Credit Risk Analytics team. This role is crucial in developing, enhancing, and maintaining the models used to forecast credit losses (Probability of Default, Loss Given Default, Exposure at Default) across our auto loan portfolio. The successful candidate will leverage a solid quantitative background, creative problem-solving abilities, and experience with a range of modeling methodologies, including traditional statistical techniques, machine learning, and artificial intelligence, to deliver robust and insightful credit loss forecasts essential for business decision-making, capital planning, and regulatory compliance.

You'll have...

Master's degree in a quantitative field such as Statistics, Economics, Mathematics, Operations Research, Data Science, Computer Science or a related discipline. Demonstrated experience in developing and implementing statistical or quantitative models, preferably in a financial services or credit risk environment. Strong proficiency in traditional statistical modeling techniques (e.g., linear and non-linear regression, time series analysis, panel data models, survival analysis, multivariate techniques). Proven knowledge of Machine Learning and Artificial Intelligence concepts and techniques relevant to quantitative modeling problems (e.g., classification, regression, time series forecasting with ML/AI methods). Experience with statistical modeling software (e.g., SAS is highly preferred; proficiency in Python or R with relevant statistical/ML libraries is also valuable). Experience querying and manipulating large datasets using SQL. Solid analytical, problem-solving, and creative thinking skills with the ability to formulate problems and propose innovative solutions. Excellent written and verbal communication skills, with the ability to effectively translate complex quantitative concepts into business terms.

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:

• 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.

For more information on salary and benefits, click here: BENEFITS

This position is a range of salary grades SG6-SG8 .

Visa sponsorship is not available for this position.

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.

Onsite work of up to three days per week may be required for candidates within commuting distance of a Ford hub location. #LI-Hybrid #LI-FordCredit 

What you'll do...

Research, develop, validate, and implement advanced statistical and quantitative models for credit loss forecasting (PD, LGD, EAD) at various levels of granularity (e.g., segment, portfolio). Explore, evaluate, and apply innovative modeling techniques, including machine learning and artificial intelligence methods, alongside traditional econometric and statistical approaches. Analyze complex credit performance data, portfolio characteristics, and macroeconomic trends from diverse data sources and platforms. Enhance and maintain existing credit loss models throughout their lifecycle, ensuring performance, stability, and adherence to model governance standards. Collaborate closely with partners in Risk Management, Finance, Accounting, and other business units to understand modeling needs, communicate model capabilities and limitations, and explain forecasting results. Translate complex quantitative analyses, modeling methodologies, and results into clear, concise, and actionable insights for both technical and non-technical audiences, including senior leadership. Support regulatory requirements related to credit loss forecasting, such as ECL/CECL (Expected Credit Loss/Current Expected Credit Loss) and stress testing, by ensuring model soundness and comprehensive documentation. Conduct ad-hoc quantitative analysis to support portfolio performance monitoring, risk assessment, and strategic initiatives. Develop and maintain comprehensive model documentation in accordance with internal policies and regulatory expectations.