Python Analytics Jobs in Buffalo, NY (NOW HIRING)

Overview:

Provides analytical and technical support for the development, refinement, and ongoing monitoring of credit risk models used to meet regulatory requirements and support the Bank's strategic risk management objectives. This includes models for loss forecasting, default probability estimation, and other creditsensitive behaviors across lending portfolios. Performs data preparation, exploratory data analysis, and model estimation under the guidance of senior modelers, leveraging strong quantitative skills and proficiency in Python, SQL, and statistical methods. Collaborates with Credit Risk Management, Model Risk Management, and business line partners to ensure model methodologies, assumptions, and outputs align with regulatory expectations and the Bank's broader credit risk framework. Communicates analytical results through clear narratives, visualizations, and documentation that support model development, validation activities, and ongoing performance monitoring.

Primary Responsibilities:

• Support the development, enhancement, and testing of credit risk models, including probability of default, loss forecasting, risk rating, and other borrowerbehavior models.
• Conduct statistical and econometric analyses using Python, SQL, and related tools to estimate, validate, and refine model components.
• Prepare, clean, and analyze largescale loan and customer datasets, ensuring data quality and readiness for modeling.
• Assist with model implementation and ongoing performance monitoring, identifying deviations and contributing to model improvements.
• Develop and maintain clear, comprehensive model documentation and performance monitoring reports.
• Communicate analytical findings through visualizations, presentations, and written summaries.
• Collaborate with Credit Risk Management, Model Risk Management, and business partners to ensure model alignment with regulatory expectations.
• Provide analytical support across the Bank and contribute to a collaborative, resultsfocused environment.

Scope of Responsibilities:

The position serves as a midlevel quantitative analyst responsible for applying statistical programming and analytical techniques to support the development, implementation, and maintenance of credit risk models. The analyst works with complex datasets and contributes to the creation of behavioral and creditsensitive models. The role requires clear communication of findings through narratives, visualizations, and technical explanations. Success requires strong attention to detail, consistent execution, and the ability to manage multiple concurrent initiatives in collaboration with teams across the Bank. The analyst must be able to identify and interpret complex business, data, and statistical issues, contributing to solutions that enhance model performance and support broader risk management objectives.

Supervisory/Managerial Responsibilities:

Not Applicable

Education and Experience Required:

• Bachelor's degree and a minimum of one year of proven quantitative behavioral modeling experience, or a combined minimum of five years of higher education and/or work experience, including at least one year of quantitative modeling experience.
• Minimum of one year of onthejob experience using statistical software packages such as SAS, Python, or R.
• Strong Python skills required.
• Model development experience required, including familiarity with logistic and linear regression techniques.
• Minimum of one year of experience working in a data management environment such as SQL Server Management Studio.
• Minimum of one year of experience managing and analyzing large datasets, with the ability to communicate results clearly using written, verbal, and visual formats.

Education and Experience Preferred:

• Master's or Doctorate degree in Statistics, Economics, Finance, or a related quantitative field.
• Minimum of two years of statistical analysis or programming experience.
• Credit model development experience, with consumer, home secured, or small business modeling preferred.
• One or more years of handson Python programming experience.
• Proficiency in econometric and statistical techniques, including paneldata methods, and logistic regression.
• Knowledge of model risk management and validation practices, including familiarity with SR 117 guidance.
• Ability to work independently and collaboratively within a team environment.
• Demonstrated leadership skills and a strong desire to learn and contribute to team objectives.

Physical Requirements:

None