Data Scientist Lead - Marketing Predictive Analytics

Leads the development, deployment, and optimization of predictive models across all Retail, Business Banking and Wealth LOBs that drive customer growth and profitability.  Owns end-to-end model lifecycle from data sourcing through validation and approval.  Direct leadership of assigned data science team.

• Develop and own predictive models, including propensity models, response models, customer value models, Marketing Mix Models (MMM) and segmentation models.
• Select appropriate methodologies (logistic regression, GBM, random forest, etc.) based on business use case.
• Communicate models with senior leaders and business partners in a clear and concise manner.
• Manage ongoing model execution, validation, enhancement and governance of model suite.
• Partner with Marketing Analytics and business partners to leverage models for targeting strategies to efficiently grow the business.
• Define and curate model-ready feature sets from internal and 3rd party data sources.
• Engineer model features that capture customer behavior, engagement, credit signals, channel interaction and channel activity.
• Leverage tools such as Databricks for MLOps.
• Ensure models are compliant with Model Risk Management (MRM).
• Lead and mentor junior data scientists
• Define modeling standards and best practices across the team.
• Drive consistent tool usage, methodologies and MLOPs processes
• Manage and develop champion/challenger models and adjust models accordingly.
• Exercise usual authority of a manager concerning staffing, performance appraisals, promotions, salary recommendations, performance management and terminations.
• Understand and adhere to the Company’s risk and regulatory standards, policies and controls in accordance with the Company’s Risk Appetite.  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.
• Complete other related duties as assigned.

Number of Staff: 6-8

• Bachelor’s degree and a minimum of 7 years related experience, or in lieu of a degree, a combined minimum of 11 years higher education and/ or work experience, including a minimum of 7 years related experience
• Minimum of 2 years managerial, supervisory and/or work leadership experience
• Intermediate experience working with multiple statistics and following data science principles such as AB testing, sample selection, hypothesis testing, and modeling bias
• Intermediate proficiency with pertinent statistical software and languages and tools
• Experience with 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)
• Expert understanding of modeling techniques such as Bayesian modeling, Classification models, Cluster analysis, Neural Network, Non-parametric methods, and Multivariate statistics
• Experience analyzing large data sets
• Proficient in data scient platform programming languages such as Python, R, SQL, SAS
• Proficient with data platforms such as Snowflake and Databricks

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
• Fluent in econometric/statistical techniques, including time-series analysis, panel data methods and logistic regression
• Tactical experience with pertinent statistical software and languages and tools

Work Model & Office Locations:

This role follows a hybrid work model, requiring onsite presence four days per week at one of M&T Bank’s regional offices. Candidates must reside within a reasonable commuting distance to one of the following locations:

• 345 Main Street, Buffalo, NY

• 115 Federal Street, Boston, MA

• 1 Light Street, Baltimore, MD

• 1350 I Street NW, Washington, DC

• 1100 North Market Street, Wilmington, DE

• 277 Park Avenue, New York, NY

• 850 Main Street, Bridgeport, CT

• 77 Pine Street, Burlington, VT