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Open nowPosted 28 days ago

Anti-Fraud Business Lead (Fintech Farm)

flyer-one-ventures8 open roles

Where
Kyiv
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Your applicationOpen nowAnti-Fraud Business Lead (Fintech Farm)flyer-one-ventures · Kyiv
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This job: posted 28 days ago

The posting

Flyer One Ventures is an early-stage venture capital fund investing in ambitious CEE and Ukrainian founders who build global companies. We’ve already invested in 95 startups and deployed nearly €40M. We focus on software-first products that use the power of tech to boost productivity. We primarily invest at seed. Occasionally, we do pre-seed, focusing on second-time founders. We are a fund of entrepreneurs who know how hard it is to build a company. Our team helps founders with growth, recruiting, PR, business development, and investment relations.

About Fintech Farm

Fintech Farm is a UK fintech company creating successful neobanks in emerging markets in partnership with local traditional banks.

Our success is built on a best-in-class product, exceptional customer experience, emotional engagement, viral growth, and deep expertise in credit decisioning.

One of our founders previously co-founded a highly successful Eastern European neobank with a multi-million customer base.

We launched our first market with Leobank in Azerbaijan in 2021, where we have already established a leading market position. In early 2023, we launched Liobank in Vietnam and achieved strong market traction. Several additional markets are planned for launch over the next 12 months, and we are building the teams that will make them successful.

About the Role

We are looking for someone who will own the fraud prevention function for a specific market — from strategy to execution and measurable outcomes.

This is not a narrow analytical role but a project leadership position. You will be responsible for how fraud prevention operates across the market, which risks it addresses, and how effectively it balances security with customer experience.

You will manage the full lifecycle: investigating fraud cases and patterns, designing fraud rules and logic, defining development requirements, overseeing testing and implementation, training operational teams, and monitoring the effectiveness of implemented solutions.

Success in this role requires both strong analytical capabilities and deep technical expertise. You should be equally comfortable working with data and understanding how systems operate under the hood.

Your decisions will directly impact fraud losses, false-positive rates, and customer trust within the market you oversee.

What You Will Do:

  • Own the fraud prevention agenda for a specific market as a project lead: objectives, roadmap, priorities, and outcomes;
  • Balance fraud protection and customer experience, using data to support decisions;
  • Align initiatives with the central Fraud team, Product, Operations, and Risk functions;
  • Create business requirements and tasks for fraud prevention logic, including rules, thresholds, trigger scenarios, and system actions;
  • Translate business goals and analytical insights into clear and actionable development requirements;
  • Maintain up-to-date documentation for fraud rules and review workflows;
  • Manage the full implementation cycle, from requirement definition to production release;
  • Participate in testing, validate rule performance, and assess results using real-world data;
  • Monitor implementation quality and respond quickly to issues after deployment;
  • Train fraud operations teams on alert handling, decision-making processes, and escalation criteria;
  • Develop procedures, playbooks, and operational guidelines;
  • Collect feedback from operators and incorporate it into rule improvements;
  • Investigate fraud incidents and cases, reconstruct attack scenarios, and identify root causes;
  • Analyze fraud patterns, identify emerging threats, and formulate mitigation hypotheses;
  • Define requirements for new fraud prevention mechanisms and drive them through implementation;
  • Monitor rule effectiveness, including fraud loss prevention, false-positive rates, and customer journey impact, and adjust configurations when necessary;
  • Independently analyze large volumes of transactional and behavioral data;
  • Write complex SQL queries, build analytical views, dashboards, and regular performance reporting;
  • Segment customer populations and identify anomalies and deviations from expected behavior.

Who You Are:

  • Strong experience in fraud prevention, transaction monitoring, or risk analytics, with a solid understanding of fraud detection systems;
  • Experience owning projects or business areas, driving initiatives from concept to delivery, and being accountable for outcomes;
  • Advanced SQL skills with the ability to independently write complex queries;
  • Experience working with ClickHouse, PostgreSQL, or similar analytical databases;
  • Deep technical understanding of transaction processing, payment systems, card products, and how fraud prevention systems operate internally;
  • Experience with mobile banking or fintech applications and a strong understanding of customer journeys in digital banking;
  • Experience defining requirements for engineering teams and supporting development and testing lifecycles;
  • Strong analytical mindset with the ability to identify patterns where others see randomness;
  • High degree of ownership and accountability, with the ability to work independently and proactively.

Nice-to-Have:

  • Experience working in banking, fintech, or payment services within emerging markets;
  • Understanding of AML/KYC regulatory requirements;
  • Experience managing fraud operations teams or cross-functional teams;
  • Familiarity with machine learning approaches in fraud prevention and basic data engineering concepts.

What We Offer

  • The opportunity to work alongside Fintech Farm's central Fraud team, bringing international expertise and best practices;
  • Competitive compensation with performance-based bonuses;
  • Flexible working arrangements;
  • Strong growth opportunities, both vertically (ML models, data engineering) and horizontally (product and business decision-making);
  • Fully remote work environment;
  • Share options.
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