Financial Model Developer - Brains WorkGroup : Job Details

Our client, a major bank in New York City, is looking for talented Financial Model Developer for Financial Resource Management (FRM) Team.Permanent position with competitive compensation package (base is 130-175K), excellent benefits, and target bonus.This is hybrid commute position with up to 2-2 days per week in the office.Financial Model DeveloperFRM seeks a quantitatively oriented individual for the position. 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; andGeneral tasks associated with managing the bank's capital position.This is a key role in developing, validating, and maintaining predictive models that estimate Pre-Provision Net Revenue and Balance Sheet forecasts for banking 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: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 Federal Reserve 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 counter-parties 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.Eligible to work in the U.S. without sponsorship.Please email your resume or use this link to apply directly: email: [email protected] ALL our Jobs: bank python sas model regression forecast risk regulatory statistics math quantitative