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AVP- CCAR Model Development

https://www.citi.com/ Logo

Citi

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Location:
India, Gurgaon

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Category:
Finance

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Contract Type:
Not provided

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Salary:

Not provided
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Job Description:

The FP&A Statistical Modeler Senior Analyst is an intermediate level position, part of FP&A Model Development team which is responsible for developing econometric time-series models to project balance sheet and income statement for different products / businesses / geographies within the firm to support CCAR and QMMF.

Job Responsibility:

  • Development of econometric forecasting models for key Balance sheet and income statement line items for capital and business planning purposes
  • Developing Champion and Challenger models using different time series forecasting methodologies to comply with SR 15-18 guidance
  • Development of Benchmark models using Industry data series to meet regulatory requirements
  • Manage the model life-cycle from first-line of defense perspective and participate in Segmentation, Risk Identification, overlay discussions with Businesses and Finance teams
  • Responsible for understanding changes to quantitative requirements published by MRM in Model Testing Guidance and presenting the key changes to senior model development leads
  • Contribute to model convergence initiatives as part of firm’s Transformation journey for different businesses
  • Responsible to explain model results to front-office / FP&A teams during quarterly model runs under different scenarios provided by Economic Scenario Group
  • Responsible in seeking sign-offs on final selected models from key stakeholder such as Business heads, FP&A head, Treasury and Risk
  • Responsible for writing model development documentation and partner with Model Risk Management (MRM) to address their feedback

Requirements:

  • 6-8 years of relevant statistical /business experience in financial services
  • Strong understanding of statistical techniques such as Ordinary Least Square regression (OLS), Fixed-effect Panel Regression, Error Correction Models, Seemingly Unrelated regression and Cointegration
  • Understanding of Machine learning algorithms will be a plus
  • Hands-on experience in programming and modeling using SAS, Python and R is preferred
  • Follow a culture of accountability and strict quality control of the data integrity and modeling process
  • Ability to build key relationships with finance and business teams
  • Must be able to present technical matters in a way that is meaningful to the audience
  • Masters / PhD in quantitative discipline such as Statistics, Economics or related discipline

Nice to have:

  • Understanding of Machine learning algorithms
  • Hands-on experience in programming and modeling using SAS, Python and R

Additional Information:

Job Posted:
March 22, 2025

Employment Type:
Fulltime
Work Type:
On-site work
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