Fraud Researcher

Description

nSure.ai is the payment fraud prevention provider of choice for Crypto, Gaming and Gift Cards. We offer a managed service based on adaptive AI that deploys, for each customer, a dedicated model trained on their data. Focusing on behavioral patterns - the most accurate and uniquely effective way to mitigate modern scalable fraud - our solution takes a fundamentally different approach to detecting fraud and preventing it from happening. Our customers benefit from the highest-efficacy decisions delivered in under 500 ms, with up to 98% approval rates and a chargeback guarantee, generating zero-risk net incremental profit.

We're looking for a Fraud Researcher to join our team at one of our offices in Tel Aviv, Bishkek, or Vilnius.

Requirements

Bachelor's degree in a quantitative field such as Statistics, Economics, Mathematics,

Industrial Engineering, or a related field — Must

● 4+ years of experience as a Fraud / Cyber / Defence analyst — Must

● Experience applying statistical techniques — Must

● Proficiency working with SQL databases — Must

● Familiarity with Python and the Pandas library — Must

● Strong analytical and investigative skills — Must

● Excellent verbal and written communication skills in English — Must

● Experience working in an operational environment — Advantage

● Creative thinker

● Detail-oriented

● Ability to work independently and manage multiple priorities in a fast-paced environment

● Team player

● Excited by startup culture and eager to join the ride

Responsibilities

As a Senior Fraud Analyst, you will lead research into emerging fraud trends, typologies, and

attack vectors to keep the company ahead of evolving threats, while supporting the detection,

investigation, and mitigation of fraudulent activity across the business. You'll conduct deep-dive

analysis across large datasets and historical fraud patterns to uncover fraud rings and behavioral

clusters that inform detection strategy, and you'll build and maintain the methodologies and

processes used to track the company's risk metrics. You will track how fraud tactics shift across

geographies and payment methods, and translate those findings into actionable insights for

internal teams building or tuning models. Strong analytical and statistical skills, comfort working

with large and messy datasets, and genuine curiosity about how fraudsters adapt are essential,

along with the ability to clearly communicate complex findings to both technical and

non-technical audiences while maintaining strict confidentiality around sensitive data.