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Wave HQ

Data Analyst, Risk

Sorry, this job was removed at 08:12 p.m. (PST) on Monday, Mar 16, 2026
Remote
Hiring Remotely in Canada
Remote
Hiring Remotely in Canada

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At Wave, we help small businesses to thrive so the heart of our communities beats stronger.  We work in an environment buzzing with creative energy and inspiration. No matter where you are or how you get the job done, you have what you need to be successful and connected. The mark of true success at Wave is the ability to be bold, learn quickly and share your knowledge generously.

The Data Analyst, Risk role is responsible for analysis and reporting that supports our Fraud & Risk Operations team and other business partners across Wave. In this role, you'll be responsible for using Risk data to deliver reporting, insights and analysis that drive decision- making for our Fraud & Risk Operations at Wave, while developing recommendations to support Wave’s lines of business.

Here's how you'll make an impact:

  • 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.

You'll thrive here if you have the following:

  • 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.

At Wave, we value diversity of perspective. Your unique experience enriches our organization. We welcome applicants from all backgrounds. Let’s talk about how you can thrive here!

Wave is committed to providing an inclusive and accessible candidate experience. If you require accommodations during the recruitment process, please let us know by emailing [email protected]. We will work with you to meet your needs.


Please note that we use AI-assisted note-taking in interviews for transcription purposes only. This helps ensure interviewers can remain fully present and engaged throughout the discussion.

This advertised posting is a current vacancy.

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