Sr. Fraud BI Analyst

The Enterprise Fraud Reporting & Analytics team is responsible for providing fraud reporting and analytics solutions that guide strategic business decisions across the organization. They collect and transform raw data into actionable fraud insights, with an emphasis toward identifying fraud trends and reducing fraud loss. They also partner with key stakeholders for developing and optimizing fraud data solutions.

As a Sr. Fraud BI Analyst, you will be designing and developing dashboards, self-service tools, reports, data models, and scalable ad-hoc reporting including driving business solutions through data analytics. This is a subset of the overall responsibilities which will include multiple initiatives assigned by Bank Operations leadership.

This role is hybrid (Mon through Thu on-site / Fri remote) for candidates in the Kansas City metropolitan area and open to qualified remote candidates outside of the Kansas City area. However, the remote location must be within the US.

How you will spend your time:

• Design and develop dashboards, self-service tools, reports, data models, and scalable ad-hoc reporting.

• Drive business solutions through data analytics; querying, mining, visualizing, and presenting data.

• Performs statistical analysis to identify trends and underlying patterns for business insights and decision making.

• Innovate KPIs, metrics, and tracking methodologies for measuring performance with the ability to communicate data insights and provide recommendations to key stakeholders.

• Collaborate with business leaders to understand business challenges that will benefit from analytics support.

• Proactively analyze data through self-initiated curiosity with an eye for operational improvement.

• Bachelor’s Degree in Data Analytics, Data Science or similar field of study OR equivalent combination of education and work experience.

• At least 5 years of data analytics experience.

• At least 5 years of report development experience using data visualization software.

• Solid proficiency in data visualization and reporting best practices.

• Strong statistical analysis experience to identify trends and patterns.

• Knowledge of extract, transform, load (ETL) data management processes.

• Solid proficiency for problem solving, analytics, and reporting.

• Ability to partner with multiple lines of business to achieve common goals.