Live opening · Posted 7 days ago
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About the role
Description supplied by the original job listing.
Job Ref ID: JR0084509
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).
You have:
1-3 years of experience in fraud prevention, risk management, fintech or analytics.
A Bachelor’s degree in Economics, Statistics, Mathematics, Engineering, or a related quantitative field.
Strong analytical skills with proficiency in SQL; familiarity with Python or other analytical tools is a plus.
Experience with BI tools such as Looker, Tableau, or similar.
Theoretical understanding of Precision vs. Recall and A/B testing principles.
Good communication and stakeholder management skills - comfortable presenting insights to both technical and business audiences.
Curiosity and a problem-solving mindset, with a desire to learn and grow within risk and fintech.
Proficiency in English.
Employment type
Full-time
Work arrangement
No
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