Senior Treasury Quantitative Analyst for Middle Office (Hybrid in Buffalo, NY)
Buffalo, NY, United States
Full Time Senior-level / Expert USD 82K - 137K
M&T Bank
With a community bank approach, M&T Bank helps people reach their personal and business goals with banking, mortgage, loan and investment services.** Work Arrangement/Location: This is a hybrid position requiring in-office work three days every week and will be based at the One M&T Plaza corporate office in Buffalo, NY.
Overview:Within M&T’s Corporate Treasury Division, a middle office function is being created to support trading activities of the bank’s balance sheet hedging, customer driven Foreign Exchange and Interest Rate derivatives, bank issued debt and portfolio securities. The position will afford the analyst an opportunity to develop hard skills in derivatives structuring, model validation under the bank’s Model Risk Management group requirements, statistical model performance monitoring and advanced data analytics
Provides independent contribution to team, including data analysis, model development efforts and ad-hoc analysis as appropriate. Provides guidance and direction to less experienced personnel.
Primary Responsibilities:
- Research and develop quantitative behavioral models used for credit risk, interest rate risk and liquidity risk management, as well as balance sheet and capital planning, including but not limited to, loan delinquency, default and loss models, loan prepayment and utilization models, deposit attrition models and financial instrument valuation methods.
- The position will afford the analyst an opportunity to develop hard skills in derivatives structuring, model validation under the bank’s Model Risk Management group requirements, statistical model performance monitoring and advanced data analytics.
- Prepare, manage and analyze large customer loan, deposit and/or financial data sets for statistical analysis in Structured Query Language (SQL) or similar tool to properly specify and estimate econometric models to understand customer or Bank behavior.
- Run regressions (including time series and logistic regression), programming routines and other econometric analyses to specify models using appropriate statistical software; communicate results, including graphic and tabular forms, to fellow team members, Treasury management and Bank-wide stakeholders, including the business lines and Risk Management colleagues to demonstrate key risk drivers and dynamics of model output.
- Execute models in production environment; communicate analytical results to Bank-wide stakeholders. Track portfolio performance, model performance, campaign tracking and risk strategy results. Incorporate observations and data into existing models to improve predictive results. Identify deviations from forecast/expectations and explain variances. Identify risk and/or opportunities.
- Develop and maintain satisfactory model documentation, including process narratives and performance monitoring guidelines to serve as reference source.
- Provide financial analysis and data support to other groups/departments across the Bank as required. Support engagements with colleagues in Model Risk Management for model validation exercises.
- Provide guidance and direction to less experienced personnel regarding all aspects of data and financial analysis and development and management of predictive statistical models.
- Conduct business in compliance with regulatory guidance including SR (Supervision and Regulation Letters) 10-1, SR 10-6, SR 11-7, Enhanced Prudential Standards, etc. Adhere to applicable compliance/operational/model risk controls and other second line of defense and regulatory standards, policies and procedures.
- Adhere to applicable compliance/operational risk controls in accordance with Company or regulatory standards and policies.
- Promote an environment that supports diversity and reflects the M&T Bank brand.
- Maintain M&T internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators as applicable.
- Complete other related duties as assigned.
Scope of Responsibilities:
The position serves as senior analyst in the use of statistical programming languages to analyze Bank datasets and develop, implement and maintain behavioral models in the newly created middle office. It is important for the position to communicate with clear narratives, compelling data visualization and technical precision, both in-person and in writing, to enable audiences to understand analysis and forecasts. The position partners and collaborates with colleagues in related functions, including Credit Risk Management, Asset Liability and Liquidity Management, Model Risk Management and business lines to develop, implement and understand models for Bank use. The position may lead team-based projects related to model development or implementation. This role is highly technical in nature and requires demonstrated attention to detail, execution and follow-up on multiple initiatives with Treasury and across the Bank. The ability to identify, analyze, rationalize, and communicate complex business, data and statistical problems and recommend corresponding solutions is a key factor of success in this role.
Managerial/Supervisory Responsibilities:
Not Applicable
Education and Experience Required:
- Bachelor’s degree and a minimum of 2 years’ proven quantitative behavioral modeling experience, or in lieu of a degree, a combined minimum of 6 years’ higher education and/or work experience, including a minimum of 2 years’ proven quantitative behavioral modeling experience
- Minimum of 2 years’ on-the-job experience with pertinent statistical software packages (SAS, Python, Stata, R)
- Minimum of 2 years’ on-the-job experience with data management environment, such as SQL Server Management Studio
- Minimum of 2 years’ experience analyzing large data sets and explaining results of analysis through concise written and verbal communication as well as charts/graphs
Education and Experience Preferred:
- Masters’ of Science or Doctorate degree in Statistics, Economics, Finance or related field in the quantitative social, physical or engineering sciences, with proven coursework proficiency in statistics, econometrics, economics, computer science, finance or risk management
- Minimum of 3 years’ statistical analysis programming experience
- Financial Risk Manager (FRM) or Chartered Financial Analyst (CFA) designation
- Fluency and high proficiency in econometric/statistical techniques, especially time-series analysis, panel data methods and logistic regression
- Experience in balance sheet management and mathematical modeling of financial instruments offered by banks
- Knowledge and familiarity with key aspects of model risk management and model validation, including SR-11-7 guidance on model risk management
- Proven track record for being able to work autonomously and within a team environment
- Demonstrated leadership skills
- Strong desire to learn and contribute to a group
Tags: Computer Science Credit risk Data analysis Data Analytics Data management Data visualization Econometrics Economics Engineering Finance ML models Python R Research SAS SQL Stata Statistics
Perks/benefits: Competitive pay
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