About the role

Data Analyst responsible for analysis and reporting for Wave’s Fraud & Risk Operations. Collaborating with teams to drive insights and decision-making based on risk data.

Responsibilities

Develop analysis and reporting to track business patterns and trends for our Fraud & Risk Operations team.
Build and deploy rules with our Risk monitoring systems in partnership with the Risk Leadership team to help detect and prevent merchant fraud, credit, and compliance risk.
Work with stakeholders across Fraud & Risk, Financial Service Operations, Customer Success, and Product to understand their challenges and goals, identifying analysis opportunities and tools to support strategic decision-making.
Take the lead on improvements to Wave’s risk infrastructure, processes and procedures to reduce losses and improve the customer experience.
Partner with fellow data analysts and data scientists to develop new analysis tools and to document best practices.
Facilitate the creation of reporting dashboards (via Looker), establishing and interpreting the performance of key metrics, and advocating for experimental best practices as we evolve the analytical maturity of the company.
Partner with Machine Learning engineers to interpret Risk ML models and share insights with business stakeholders.
Extract and transform data for use by stakeholders, ensuring data integrity in partnership with our Data Engineering team.

2+ years of experience in merchant Fraud & Risk Analytics, with payments fraud experience preferred.
Degree in Mathematics, Statistics, Economics, Data, or a related quantitative field.
Strong SQL skills with experience querying large and complex datasets.
Working knowledge of fraud and/or credit underwriting/adjudicating, with experience working in a payments or Fintech space.
Financial Services experience, especially with Payments, Payroll, Banking, or Accounting industries.
Previous experience developing reports and dashboards with Looker (or equivalent data visualization platforms).
Ability to effectively communicate complex matters and requirements between audiences, both visually and verbally.
Proactive, autonomous, and able to partner with business and engineering stakeholders to support the delivery of key projects.
Possess business acumen to identify and evaluate key performance indicators and provide recommendations that drive decision-making and propel business value.
Experience with Python for data analysis is an asset.
Experience using dbt to transform and deploy data models an asset.