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Plooto Inc. is seeking a Risk Decision Scientist to optimize payment risk decisioning using data, experiments, and decision-science techniques.
You will analyze risk rules, thresholds, customer segments, and review strategies to reduce manual reviews while maintaining strong loss performance. Collaborate with Risk Operations, Product, Engineering, and Data teams to translate analysis into practical improvements.
The Risk Decision Scientist will support the ongoing optimization of Plooto’s payment risk decisioning, using data, experimentation, and decision-science techniques to help reduce unnecessary manual reviews while maintaining strong loss performance.
This role will analyze the performance of risk rules, thresholds, customer segments, and review strategies and identify opportunities to improve decision precision. Working closely with Risk Operations, Product, Engineering, and Data, the successful candidate will turn analysis into practical recommendations that reduce customer friction and help Plooto’s risk controls scale as payment volume grows.
You'll help lay the foundation for how Plooto hires during our next stage of growth.
You'll shape recruiting strategy, influence leaders across the company, experiment with AI-native ways of working, and build hiring practices that will have a lasting impact long after your engagement is complete.
If you're energized by building, coaching, finding remarkable people, and leaving things better than you found them, we'd love to meet you.
Plooto is committed to building an inclusive workplace where people of all backgrounds, experiences, and perspectives can thrive. We know that great teams are built through diverse thinking, and we encourage you to apply even if your experience doesn't align perfectly with every qualification listed.
Accommodation is available throughout the recruitment process in accordance with applicable accessibility legislation. If you require accommodation at any stage, please let us know—we're happy to work with you.
This posting is for one available position. Compensation will be determined based on the successful candidate's knowledge, skills, experience, and overall alignment with the role.