Quick Summary
MSc or PhD in Computer Science, Engineering, Applied Math, Physics, Statistics, or another technical/quantitative discipline; Strong background in data science, fraud detection, or real-ti
At Feedzai, we're building a world of safer money. A world where financial institutions move faster than criminals. Where the payments that fund real lives through salaries, savings, and businesses are protected in real time. We use trusted AI to detect and prevent financial crime, fraud, and money laundering at scale: the world's top banks, payment networks, and acquirers trust our technology to safeguard more than one billion consumers and $9 trillion in payment volume every year.
Feedzai is a Series D company and has raised $282M to date. With a valuation of $2 billion, our technology protects 1 billion consumers and 90 billion transactions each year.
We are looking for a highly motivated and technically strong leader to join our Customer Success organization as a Risk & AI Manager. You will lead a cross-functional team of Risk Consultants, Data Scientists, and Business Analysts who work side-by-side with some of the world’s largest financial institutions and merchants to help them fight fraud and unlock the full value of Feedzai’s platform.
Your team’s mission is to ensure clients extract measurable value from Feedzai by delivering optimized fraud strategies, machine learning models, business-aligned risk logic, and data insights. You will manage a portfolio of high-impact client projects, lead technical and strategic decision-making, and grow a team of domain experts and problem solvers who understand both the product and the business.
- Lead a distributed team of Risk Consultants, Data Scientists, and Business Analysts across multiple client engagements (typically 6–8 active projects);
- Ensure the delivery of fraud detection strategies, rules, models, and analysis that meet client goals and align with Feedzai's best practices;
- Translate complex business objectives into data-driven solutions and clear technical action plans;
- Guide the integration and validation of Feedzai’s real-time and batch analytics into client environments;
- Support your team in identifying misfit cases, scoping performance improvements, and proactively recommending enhancements;
- Collaborate with Engineering, Product, and Delivery to align on scope feasibility, performance requirements, and long-term strategy;
- Mentor your team, manage performance reviews, and support professional development through feedback, coaching, and career planning;
- Stay current with fraud patterns, machine learning best practices, and how they apply in real-world financial systems.
- MSc or PhD in Computer Science, Engineering, Applied Math, Physics, Statistics, or another technical/quantitative discipline;
- Strong background in data science, fraud detection, or real-time decision systems;
- Hands-on experience with machine learning, data analysis, and scripting languages such as Python or R;
- Familiarity with big data platforms such as Spark, Hadoop, or cloud-native data pipelines;
- Experience managing technical teams in cross-functional delivery environments;
- Ability to navigate ambiguity, translate between technical and business needs, and prioritize effectively under pressure;
- Excellent communication and storytelling skills — able to work with both client SMEs and Feedzai's internal stakeholders;
- Experience in financial crime prevention (fraud, AML, risk strategy) is highly valued;
You will be immersed in our brand with training, connections, and one-on-one time with your manager. You may shadow your colleagues virtually or onsite at an office depending on where you work as you are supported through your Feedzai journey. In addition, you will have access to a ton of information to give you history, context, and all the knowledge you can handle about Feedzai and the team. Finally, you will start working on projects and collaborating on work currently being done. We can't wait to have you join the team!
Location & Eligibility
Listing Details
- Posted
- September 28, 2026
- First seen
- September 28, 2026
- Last seen
- September 28, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 76%
- Scored at
- September 28, 2026
Signal breakdown
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