Job Ref ID:JR

Be a part of a team where you will:

- Identify opportunities to reduce fraud losses on different streams and improve overall profitability by leveraging advanced risk rules and Machine Learning.

- Implement end-to-end fraud prevention strategies—design controls, execute rollouts, measure impact, and iterate for continuous improvement.

- Support the evaluation of fraud prevention controls by assisting in the setup, monitoring, and performance analysis of A/B tests.

- Collaborate with stakeholders like Product, Engineering, Data Science to propose innovative and preventive fraud controls.

- Perform risk analysis using SQL, Python and analytics platforms (e.g. Looker, BigQuery) to identify emerging fraud patterns and monitor key metrics.

- Contribute to machine learning workflows by partnering with Data Science:



define relevant features, validate model outputs, and flag performance drift.

- Maintain and optimize a centralized escalation process for suspected fraud, ensuring timely reviews, feedback loops, and alignment with local teams to adapt risk controls regionally.

- Develop and maintain executive dashboards in Looker to track fraud OKRs, financial exposure, and compliance metrics.

- Drive clarity and resolve ambiguity on complex fraud topics, using data-driven approaches, simplifying concepts for different audiences (local ops, senior leadership, or external partners).

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