OVERVIEW:

Works under limited supervision to build systems and models to analyze diverse big data sources to generate insights and solutions for business partners and product enhancement. Develops, tests and validates models that drive business value.

POSITION RESPONSIBILITIES:

• Work with data sets to solve structured problems using different analytical and statistical approaches for a single product.
• Complete sourcing, ingesting, and cleaning of data sets in preparation for analysis.
• Build statistical and machine learning models for various problems inclusive of classification, clustering, pattern analysis, sampling, and simulations.
• Commit code into model repository and promote models into production systems following more experienced team members’ guidance as required.
• Participate in the development of champion/challenger models.
• Select and refine models under guidance of a more experienced team member, accounting for performance, reliability and stability metrics and business feedback.
• Create model outputs for business discussions to display model outcomes, impact and business value.
• Complete exploratory analysis to inform development of new modeling approaches.
• Review own code to ensure it is efficient, accurate, and using 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.
• 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.

NATURE AND SCOPE:

MANAGERIAL/SUPERVISORY RESPONSIBILITY:

None

MINIMUM QUALIFICATIONS REQUIRED:

• A combined minimum of 6 years higher education and/ or work experience
• Coursework in statistics or data science principles, such as AB testing, sample selection, hypothesis testing, modeling bias.
• Basic proficiency with pertinent statistical software and languages and tools
• Understanding of various hybrid databases both on premise and in the cloud
• Intermediate level knowledge of Structured Query Language (SQL) and Not Only Structured Query Language (nSQL)
• Basic experience utilizing qualitative and quantitative analysis techniques

IDEAL QUALIFICATIONS 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
• Experience analyzing large data sets
• Working knowledge of econometric/statistical techniques, especially time-series analysis, panel data methods and logistic regression

PHYSICAL REQUIREMENTS:

Location