Hybrid Data Scientist — BI Dashboards, AI & Automation

M&T Bank; Wilmington (DE); Hybrid; USD 136,000 - 227,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

M&T Bank in Wilmington, DE is seeking an analytical leader to drive data-driven insights through dashboards, reports, and automated analytics. You will manage BI design, data modeling, and validation to support risk management decisions while promoting data quality and governance.

Responsibilities include developing best practices, publishing dashboards, enabling self-service analytics, and leveraging AI tools to enhance reporting efficiency and accuracy.

Qualifications

• Bachelor's degree and 7+ years related experience, or 11 years combined education/work experience
• Experience designing advanced dashboards and data visualizations
• Proficiency in SQL to analyze, extract, and transform data
• Experience with data quality, metric validation and governance

Responsibilities

• Develop and implement best practices for analytics, reporting, data visualization, and automation
• Publish BI dashboards/reports and analyze adoption and usage trends
• Provide ad-hoc analysis access and train users on tools
• Query, structure, transform, and model data for dashboards and analytics
• Ensure data accuracy and reliability through data management concepts
• Develop descriptive, diagnostic and predictive reporting with appropriate visuals
• Maintain templates and visual standards aligned to audience and governance
• Drive continuous improvement in dashboards and reports
• Collaborate with data stakeholders to gather visualization requirements
• Leverage AI tools to automate reporting and validate data

Skills

Data visualization

SQL

Leadership

Education

Bachelor's degree

Tools

Power BI

Python

Power Automate

Job description

M&T Bank in Wilmington, DE is seeking an analytical leader to drive data-driven insights through dashboards, reports, and automated analytics. You will manage BI design, data modeling, and validation to support risk management decisions while promoting data quality and governance.

Responsibilities include developing best practices, publishing dashboards, enabling self-service analytics, and leveraging AI tools to enhance reporting efficiency and accuracy.