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Manager, Fraud Data Team

Chainalysis Careers

Tel Aviv, Israel permanent

Posted: November 19, 2025

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Job Description

Our Alterya team is focused on AI-powered fintech and threat intelligence, empowering institutions to protect individuals from fraud transactions. The Fraud Data team understands how to transform complex fraud-related datasets into clear, actionable intelligence that protects our customers and supports critical business decisions. We’re passionate about using data, analytical models, and cutting-edge detection techniques to stay ahead of emerging fraud trends.

As the Manager of the Fraud Data Team, you’ll develop a deep understanding of our fraud frameworks, data pipelines, analytics methodologies, and detection models. You’ll guide a team of analysts to build robust fraud insights, scale detection capabilities, and support both internal and external stakeholders.

In this role, you'll:

• Lead a team of analysts responsible for researching scams and fraud patterns, and operationalizing those insights into scalable detection pipelines.

• Design and define the company’s fraud-related data structures — including data collection, normalization, enrichment, and quality standards.

• Conduct deep analysis on fraud trends, behavioral patterns, and emerging threats, turning findings into actionable intelligence for internal teams.

• Support internal and external data needs across Fraud, Risk, Product, Engineering, Customer Success, and Compliance.

• Build and maintain dashboards, monitoring tools, and metrics that improve pipeline quality, data quality, and visibility into fraud trends.

• Translate business and investigative requirements into clear technical data designs, schemas, and analytical models.

• Collaborate with Product and Engineering teams to integrate fraud logic, data features, and detection insights into platform capabilities.

• Communicate complex fraud concepts and analytical findings in an understandable way to investigators, leadership, and customer-facing teams.

• Drive continuous improvement in fraud detection logic, expand coverage across scam scenarios, and proactively identify new areas of development.

• Maintain strong data governance, documentation, and integrity for all fraud-related datasets and processes.

We're looking for candidates who have:

• Hands-on experience with SQL databases, Python, data warehousing platforms, and a background in analytics.

• Experience managing data pipelines, ETL workflows, or real-time monitoring systems.

• Demonstrated success in building and managing a high-performing data or analytics team.

• Ability to communicate complex analytical concepts clearly to executives, customers, and cross-functional partners.

• Fluency in English and Hebrew

Nice to have experience:

• Familiarity with machine learning concepts and their application to fraud detection (nice to have)

• Understanding of cloud

About Chainalysis

Blockchain technology is powering a growing wave of innovation. Businesses and governments around the world are using blockchains to make banking more efficient, connect with their customers, and investigate criminal cases. As adoption of blockchain technology grows, more and more organizations seek access to all this ecosystem has to offer. That’s where Chainalysis comes in. We provide complete knowledge of what’s happening on blockchains through our data, services, and solutions. With Chainalysis, organizations can navigate blockchains safely and with confidence.

You belong here. 

At Chainalysis, we believe that diversity of experience and thought makes us stronger. With both customers and employees around the world, we are committed to ensuring our team reflects the unique communities around us. We’re ensuring we keep learning by committing to continually revisit and reevaluate our diversity culture.

We encourage applicants across any race, ethnicity, gender/gender expression, age, spirituality, ability, experience and more. If you need any accommodations to make our interview process more accessible to you due to a disability, don't hesitate to let us know. You can learn more here. We can’t wait to meet you.

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