Analytics Scientist
About The Position
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. 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.
Requirements
- Highly motivated and quantitatively skilled
- Solid quantitative background
- Creative problem-solving abilities
- Experience with a range of modeling methodologies, including traditional statistical techniques, machine learning, and artificial intelligence
Responsibilities
- Developing, enhancing, and maintaining models used to forecast credit losses (Probability of Default, Loss Given Default, Exposure at Default) across our auto loan portfolio.
- Leveraging 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.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
