Job Description :

APN Consulting has an immediate need for a direct client requirement:
Role: Financial Data Modeler
Duration: FTE/Direct Hire
Location: 2-3 days in the office, specifically Monday & Wednesday in NYC
JOB DESCRIPTION:
General Department Description
The Financial Resource Management Unit (FRM) is responsible for estimating, reporting and managing capital and other financial indicators across Customer.
Summary
FRM seeks a quantitatively oriented individual for the position of Assistant Vice President / VP. You will serve as a subject matter expert supporting. projects in numerous areas including:

  • Developing and enhancing income statement and balance forecast models.
  • Liaising with banking and trading counterparts to manage and access the modeling data infrastructure.
  • Preparing high quality/robust model documentation and interfacing with Model Validation.
  • General tasks associated with managing the bank's capital position.
  • You will assume a key role in developing, validating, and maintaining predictive models that estimate Pre-Provision Net Revenue and Balance Sheet forecasts for our trading and banking businesses.

The ideal candidate will possess a strong understanding of how these businesses generate revenue, the associated risks, and the regulatory requirements surrounding model development and validation.
You should also posses a proven record of collaborative team engagement and a commitment to take on unfamiliar tasks and learn new topics.
Responsibilities
The candidate will provide substantial contributions to the following activities:

  • Develop and implement robust PPNR models, including revenue forecasting and risk assessment for banking and trading operations.
  • Analyze and understand the revenue-generating activities of trading and banking businesses, including interest income, fee income, and trading gains.
  • Identify and quantify risks associated with revenue generation, including market risk, credit risk, operational risk, and liquidity risk.
  • Conduct model validation and performance monitoring to ensure accuracy and compliance with regulatory standards.
  • Stay current with industry trends, regulatory changes, and best practices in model development and risk management.
  • Participate in development, maintenance, and documentation of finance models via OLS regression and A(R) approaches in accordance with Client SR 11-7 requirements.
  • Evaluate data to identify necessary adjustments and work closely with business users to create robust forecasting models and historical analyses.
  • Manage projects and deepen relationships with internal and external counterparties to enhance institutional knowledge to support the forecasting/capital management processes.
  • Ad hoc analyses to solve new problems which may require iterative analyses and dealing with potential uncertainty.


Qualifications

  • 5-7 years of relevant work experience in the financial services industry.
  • Significant knowledge and experience with statistical software (E.g. Python, SAS, etc.) as well as Microsoft Excel in a business environment.
  • A high level of flexibility and dedication to collaborating on team goals in an environment with potential changing conditions, and deadlines.
  • Robust understanding of statistical concepts, regression-based forecasting models and time series analysis.
  • Ability to effectively analyze large data sets and identify patterns and insights.
  • Strong understanding of banking and trading revenue streams, including the ability to analyze complex financial products.
  • Familiarity with risk management principles and practices in financial institutions.
  • Good communication skills (presentation and written) with an ability to explain underlying drivers and key takeaways from modeled data outputs to technical and non-technical audiences.
  • Knowledge of relevant regulatory requirements (e.g., Basel III, Dodd-Frank, SR 11-7) is a plus.
  • Candidates with a Bachelor's degree in areas such as Statistics, Financial Engineering, Econometrics, Mathematics, Finance, Engineering or other advanced quantitative field. Masters a plus.
             

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