Overview

As a Senior Fraud Data Analyst, you will be responsible for researching and identifying fraud trends and future threats. You will focus on executing methodologies and processes to track and maintain the company's risk metrics in parallel to serving superb performance to our clients. You will also be responsible for detecting risk trends and leading the frontier of various types of fraud-fighting using the most advanced technologies, methodologies, and techniques.

Key responsibilities

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    Track fraud trends by analyzing accounts and transaction patterns.
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    Analyze deep transactional and behavioral data patterns and trends and provide data insights.
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    Research reasons for deviation from baseline, and collaborate with data science teams for taking corrective measures.
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    Identify and foreseen future fraud trends and patterns.
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    Observe customer transactions to identify fraudulent activity.
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    Design and develop analytics infrastructure for researching scalable fraud.

Required experience

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    Bachelor’s degree from exact-sciences-related areas such as Statistics, Economics, Mathematics, Industrial engineering, Computer Science, or a related field.
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    Master's degree and or an active student for a Master’s degree - worked on, or actively working on a thesis - an advantage
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    At least 4 years of experience as a data analyst.
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    Experience in fraud/risk analysis in payment fraud
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    Experience in one of the following domains; Gaming, Gift cards, or Crypto- an advantage
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    Significant experience in applying statistical techniques.
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    Strong proficiency in working with SQL databases.
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    trong proficiency in Python and the Pandas package.
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    Understanding of general concepts in the field of Machine Learning - an advantage.
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    Excellent expression skills both verbal and in writing in English are a must.
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    Operative and creative thinking.
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    Ability to work in an operational, dynamic, multitasking environment.
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    Team player.
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    Someone who loves the startup spirit and would like to join the ride.

Bonus points

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    Experience with Big Data technologies such as Hadoop, Spark, or Kafka.
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    Familiarity with data visualization tools like Tableau, Power BI, or similar.
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    Knowledge of regulatory compliance related to fraud detection and prevention.
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    Hands-on experience with real-time fraud detection systems.
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    Proficiency in R or other statistical programming languages.
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    Experience with cloud platforms like AWS, Azure, or Google Cloud.
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    Background in cybersecurity or understanding of threat intelligence.

To apply

Send your CV, a snappy cover letter which highlights your expertise, skills and experience and any relevant links/attachments to your work.

Apply here

Have questions?Write to us

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