VP- CCAR Model Developer, Citi

VP- CCAR Model Developer

Citi

Location:

India, Mumbai ▼

Gurgaon

Category:

Finance

Contract Type:

Not provided

Salary:

Not provided

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Job Description:

The FP&A Statistical Modeler Sr. Manager is a senior 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
Participate and contribute to FRB / OCC exams and present model specific information to seniors in a succinct manner
Development of Benchmark models using Industry data series to meet regulatory requirements
Drive model convergence initiatives as part of firm’s Transformation journey for different businesses
Explain quantitative model results to front-office / FP&A teams during quarterly model runs under different scenarios provided by Economic Scenario Group
Responsible for exploring application of alternate modeling techniques to facilitate model convergence efforts and presenting the same to senior model development leads
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 in managing complex conversations and to seek sign-offs on final selected models from key stakeholder such as Business heads, FP&A head, Treasury and Risk
Responsible for writing and submitting model development documentation and partner with Model Risk Management (MRM) to address their feedback

Requirements:

8-10 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
Understanding of Consumer / Wholesale business to facilitate model convergence initiatives 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
Understanding of Consumer / Wholesale business to facilitate model convergence initiatives

Additional Information:

Job Posted:

March 21, 2025

Employment Type:

Fulltime

Work Type:

On-site work

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