Ford Motor Company is one of the leading Automobile and Mobility Company. Ford is into shaping Great products, Robust Business and more importantly building a Better world. The Global Data Insights and Analytics (GDI&A;) department at Ford Motor Company is looking for motivated and talented individuals to develop credit risk models for Ford Credit team.

Potential candidates should have knowledge in general math modeling, Machine Learning (ML) and related Operations Research (OR) and simulation techniques. Candidates should have hands-on experience in developing quantitative models. They should possess the ability to translate a business problem into an analytical problem, recommend, implement and validate quantitative models, and generate/deliver insights to stakeholders.

Preference would be given to candidates that are intellectually curious, creative thinkers, and have demonstrated ability to solve problems independently.

Roles & Responsibilities
Develop and validate credit risk models
Using SAS, R, Python for model building and model validation
Continual enhancement of statistical techniques and their applications in solving business objectives
Compile and analyze the results from modeling output and translate into actionable insights




Prepare PowerPoint presentations and document preparation for the entire credit risk modeling process
Collaborate, Support, Advise and Guide in development of the models
Acquire and share deep knowledge of data utilized by the team and its business partners
Participate in global conference calls and meetings as needed and manage multiple customer interfaces
Execute analytics special studies and ad hoc analyses
Evaluate new tools and technologies to improve analytical processes
Set own priorities and timelines to accomplish projects (accountability for project deliverables)
Ph.D. or Masters in Mathematics/Statistics/Economics/Engineering or any other related discipline or a track record of performance that demonstrate this ability
Practical applications of mathematical modeling, Operations Research and Machine Learning techniques
Valuable exposure to ML techniques such as Clustering/classification/decision trees, Random forests, Support vector machines, Deep Learning, Neural networks, Reinforcement learning, and related algorithms
Demonstrated knowledge in credit and/or market risk measurement and management
Excellent problem solving, communication, and data presentation skills
Proficient with SAS, SQL

📌 Credit Risk Modeler Chennai
🏢 Ford Global
📍 Chennai