Senior Quantitative Modeler, Information And Technology Industry Senior Quantitative Modeler, Information And  …

Capitalsource
in Brea, CA, United States
Permanent, Full time
Be the first to apply
Competitive
Capitalsource
in Brea, CA, United States
Permanent, Full time
Be the first to apply
Competitive
Senior Quantitative Modeler, Information And Technology Industry
Senior Quantitative Modeler (Brea, CA)

Brea, CA, USA

Accounting Finance

The Sr. Quantitative Modeler position works within the Financial Planning & Analysis (FP&A) Quantitative Analytics team and will develop quantitative/statistics models used for Current Expected Credit Loss (CECL) and stress testing purposes.

 RESPONSIBILITIES:    

  • Obtain and conduct data analysis required for stress testing model development
  • Developing and executing primary and benchmark models for credit risk and PPNR
  • Perform all required tests and measures of developed models (e.g., sensitivity, accuracy, volatility)
  • Perform routine analysis for model performance monitoring and model review, maintaining current model inventory for validation and audit compliance.
  • Deliver comprehensive model documentation (e.g., model development documents, model approval packages, technical review documents)
  • Utilize quantitative skills to analyze and summarize data, formulate findings, and provide recommendations. Research and recommend enhancements
  • Assist others with conducting business research by gathering data, identifying options, and creating non-routine reports with detailed analyses
  • Perform additional duties as required 

POSITION REQUIREMENTS: 

  • This position requires a minimum of Master’s degree in Mathematics, Statistics, Economics, Operations Research, or related field
  • Minimum 2 years of experience in the job offered or as a Predictive Analyst, or in related position. Experience must include:
    • Programming in a statistical software package such as R,SAS, or Python
    • Querying data from a data warehouse with relational database using SAS/SQL
    • General use of Microsoft Office applications (Excel, Word, PowerPoint)
    • Handle and perform large scale data manipulation using R and SAS
    • Statistical modeling techniques such as linear regression, generalized linear regression, logistic regression, time series, decision trees, cluster analysis
    • Working in cross functional teams

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