How will you make an impact?
- Analyze transaction data and customer behavior to identify patterns indicative of fraudulent activity.
- Develop and deploy data-driven fraud prevention rules, logic, and models to mitigate risk effectively.
- Continuously monitor and refine existing fraud detection models based on emerging trends and feedback.
- Design and implement automation solutions to enhance fraud monitoring processes and support scalability.
- Communicate with clients and partner banks to align on fraud prevention strategies and share actionable insights.
- Work with product and dev and other teams in Unit to lead and deliver strategic and complex projects in the Fraud prevention domain.
Have you got what it take:
- At least 5 years of experience in data analysis, preferably in the risk or fraud domain within the fintech industry.
- High proficiency in SQL – Must. Experienced in writing complex queries and analyzing large datasets.
- High proficiency in Python for data analysis – Must. Skilled in using Python libraries such as Pandas for data analysis and research, automation, and developing fraud detection logic.
- High proficiency in English and Strong written and verbal communication skills to effectively interact with clients, partners, and internal teams.
- Advantage: Understanding of the US financial systems – Familiarity with banking, payments, or e-commerce systems and processes.
- Advantage: Experience with financial fraud prevention strategies.
- Advantage: Ability to work independently, take initiative, and drive projects from ideation to completion.
- Great team player with desire to mentor junior analysts and Data scientists.
Manager
Individual Contributor