Manager, Enterprise Fraud Modeling and Analytics

Remote, WA

About BECU

BECU is Washington's largest credit union and one of the top five financial cooperatives in the country with over one million members.

We are a member-owned, not-for-profit financial institution committed to providing affordable and responsible financial services to residents of Washington State.

Since 1935, we have operated with the promise of returning value to our members in the form of better rates and fewer fees—staying true to the credit union guiding principle of "people helping people."

In the spirit of “people helping people,” BECU and employees are committed to community outreach in the areas of affordable housing, financial literacy, education support and the credit union movement.

Manager, Enterprise Fraud Modeling and Analytics


The Manager Enterprise Fraud Modeling and Analytics is responsible for the development, deployment, and monitoring of quantitatively based fraud reporting and risk mitigation/management solutions used by the credit union.  This person will manage fraud solution development independently and through collaboration with stakeholders throughout the credit union.  


  • Perform all responsibilities in accordance with BECU Competencies, compliance, regulatory and Information Protection requirements.
  • Actively collaborate with cross-functional business partners and analytics teams to design and generate advanced analytics and machine learning solutions.
  • Provide direction and thought leadership for development and maintenance of data environments supporting the credit union’s fraud reporting and analytic needs.
  • Provide analytic and strategy support for BECU’s fraud mitigation and management strategy in areas such as quantifying fraud risk appetite and tolerance relative to risk mitigate effectiveness, mitigation strategy false positive rate, and member experience.
  • Work closely with business partners to address data management and reporting needs and develop /implement quantitatively based fraud mitigation solutions, including data acquisition, model development, and production deployment.
  • Develop fraud prediction models leveraging supervised and unsupervised development methods and diverse data sources.
  • Development of a comprehensive knowledge of BECU data and core fraud systems.
  • Management of a fraud analytic initiatives pipeline. Proactively plan and prioritize work according to criticality and shifting priorities/strategies, while balancing need to drive longer-term initiatives.
  • Make recommendations and provide updates via written and verbal communication to analytical and executive business audiences.
  • Provide thought leadership on model deployment and business rule management platform considerations that underlie the execution of BECU fraud strategies.
  • Interface with external vendors in the evaluation of vended fraud risk mitigation solutions to determine suitability for possible use by BECU.
  • Establish and maintain risk modeling policies and procedures to ensure consistency of application across business use cases. 
  • Maintain a thorough knowledge relating to fraud trends and composition, while analyzing and presenting model outputs.
  • Identify opportunities for efficiencies and effectiveness, including reporting requirements.
  • Develop and maintain model documentation, change control documentation, and strategy validation documentation.
  • Build and manage a team of analytic staff supporting risk modeling activities. Provide ongoing coaching, mentoring and training within the department to develop and encourage employee performance.  Meet with staff on a timely basis for the purpose of conducting Quarterly Performance and Year-End Reviews.
  • Perform other duties, as assigned.


  • Bachelor’s degree required (Master's degree preferred), or equivalent work experience, in statistics, mathematics, engineering, computer science, physics, economics, or related quantitative discipline.
  • Minimum 4 years of experience in general modeling and analytics with 1-2 years in fraud or risk management preferred. Experience in analytics and modeling or relevant area preferable.
  • Minimum 2 years people management experience preferred.
  • Advanced understanding of statistical modeling, data mining concepts, machine learning, and experience in solving complex problems with these disciplines.
  • In-depth knowledge of the consumer financial services or payments industries, threat landscape, fraud management concepts and practices, and performance implications of policy or strategy actions preferred.
  • Experience in Azure Cloud based data structures preferred.
  • Excellent analytical and problem-solving skills required.
  • Proficient knowledge of statistical analytical packages such as SAS, Stata, DataBricks and/or R, Python, and SQL required.  Knowledge of machine learning and artificial intelligence applications preferred.
  • Proficient verbal and written skills to effectively communicate.
  • Effective leadership and negotiation skills required.
  • Full time hours required with additional hours as necessary.