Data Scientist - Forecasting

Ford Motor Company
Dearborn - United States
S: Competitive

Position Overview:

High-potential Statistical/Quantitative Analyst needed to assist in all phases of model development, evaluation, and deployment for use in support of Ford Credit business units. Individual would have a great deal of autonomy in conducting research and selecting desired modeling methodology.

Responsibilities:

Research and develop Value-at-Risk (VaR) type models to quantify exposure to credit risk
Research and improve on existing forecast models of expected credit and residual risk
Support securitization through risk analysis and reporting
Conduct process control and model validation
Work with various data sources and platforms (PC, Mainframe, Unix/Linux, Teradata) to gather data
Execute both descriptive and inferential ad hoc requests in a timely manner
Communicate and present models to business customers and executives

Minimum Qualifications:

Graduate Degree in a quantitative field
2+ years of programming experience, to include experience in either R, S plus, SAS or Matlab
2+ years of modeling experience (linear and non-linear)

Preferred Qualifications:

Demonstrated experience conducting statistical analysis in a business or academic environment
Experience in Banking/Financial industry, specifically in the area of regulatory or economic capital requirements, a plus
Experience in maximum likelihood estimation, causal inference, density estimation, time series forecasting, stochastic processes, survival analysis, and multivariate techniques such as PCA, factor analysis and cluster analysis
Ability to translate complex quantitative methods into easily understood results for all levels of business customers
Ability to handle multiple projects within a given timeframe
Strong oral and written communication skills
Some SQL programming experience
Experience with Microsoft Excel, PowerPoint and Word

Job summary