Credit Model Development Data Architect Expert

*** Work Arrangement/Location: This is a hybrid position requiring in-office work four days every week. Ideally the position will be based in Buffalo, NY but may be in an M&T office in Baltimore, MD, Bridgeport, CT, NYC, NY, Iselin, NJ, Boston, MA, Wilmington, DE, Washington, DC, or possibly another M&T Bank corporate office.

There might be potential for a remote work arrangement depending upon the location of the final candidate.

Overview:

Develops and builds complex systems of models to analyze diverse big data sources to generate insights and solutions for business partners and product enhancement. Leads work to develop, test and validate models that drive business value. Identifies, interprets, and communicates insights from data to management. Mentors less experienced team members.

Primary Responsibilities:

• Work to solve the most challenging data related problems using different analytical and statistical approaches across the organization
• Mentor less experienced data scientists on current industry best practices for preventing data drift and sourcing, ingesting, and cleaning data.
• Build complex econometric, statistical and machine learning models for various problems inclusive of classification, clustering, pattern analysis, sampling, and simulations.
• Commit complex code into model repository to serve as a source for other team members and provide feedback on other code in the repository.
• Lead the development of complex champion/challenger models and adjust models accordingly. Develop and implement framework for building self-healing models.
• Select and refine complex models, taking into account performance, reliability and stability metrics as well as business feedback.
• Leverage model outputs to identify actionable insights, suggest recommendations and influence the direction of cross-functional groups by effectively communicating model outcomes, impacts and business value.
• Guide and train less experienced data scientists on model development, selection, refinement, measurements and visualizations.
• Own relationship with data clients to understand their unique research questions and lead development of new research approaches including adaption of research techniques based on client needs.
• Lead code review to ensure code is efficient, accurate, and leveraging industry best practices.
• Understand and adhere to the Company’s risk and regulatory standards, policies and controls in accordance with the Company’s Risk Appetite. Identify risk-related issues needing escalation to management.
• Design, implement, maintain and enhance internal controls to mitigate risk on an ongoing basis. Identify risk-related issues needing escalation to management.
• Promote an environment that supports belonging 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.

Scope of Responsibilities:

The position serves as a quantitative expert in use of statistical programming languages to analyze Bank datasets and development, implementation and maintenance of behavioral models. 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 implement and understand models for Bank use. The position often leads 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 within Treasury and across the Bank. The ability to identify, analyze, rationalize and communicate complex business, data and statistical problems and recommend corresponding solutions while directing the work of others on the team is a key factor of success in this role. The position may supervise the work of interns and/or lead teams on a project basis, providing performance feedback to management as appropriate. The position also provides guidance and direction to less experienced personnel.

Education and Experience Required:

• Bachelor’s degree and a minimum of 6 years’ proven quantitative behavioral modeling experience, or in lieu of a degree, a combined minimum of 10 years’ higher education and/or work experience, including a minimum of 6 years’ proven quantitative behavioral modeling experience
• Minimum of 6 years’ on-the-job experience with pertinent statistical software packages (SAS, Python, Stata, R)
• Minimum of 6 years’ on-the-job experience with data management environment, such as SQL Server Management Studio
• Minimum of 6 years’ on-the-job experience analyzing large data sets and explaining results of analysis through concise written and verbal communication as well as charts/graphs
• Experience with various hybrid databases both on premise and in the cloud
• Experience analyzing and explaining results of large data sets analyses

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 8 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

Proven leadership skills

Strong desire to learn and contribute to a group

Previous experience leading and directing the work of less experienced personnel

Location