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Senior Fraud Data Analyst

At Trustly · Stockholm; Lisbon

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Where you’ll work

Hybrid, based in Lisbon or Stockholm

“Stockholm”

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“Lisbon”

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The job board lists it as hybrid.

Hybrid means some days in the office. The listing says how many, and where.

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Posted
20 October 2026
First seen by us
21 October 2026
Last checked
23 hours ago

Job description

From Trustly’s job post, as they wrote it.

WHO WE ARE

At Trustly, we're building a smarter, faster, and more secure financial future by revolutionizing the world of payments. As a global leader in Open Banking Payments, we are establishing Pay by Bank as the new standard at checkout, providing unparalleled freedom, speed, and ease to millions of consumers and merchants worldwide.

Our Ambition: To build the world’s most disruptive payment network and redefine what the payment experience should feel like.

Read the full description

Trustly is a global team of innovators, collaborators, and doers. If you are driven by a strong sense of purpose and thrive in a dynamic, entrepreneurial, and high-growth environment, join us and be part of a team that’s transforming the way the world pays.

ABOUT THE ROLE

As a Senior Fraud Data Analyst within Trustly’s Risk Precision team, you take ownership of fraud risk performance in Trustly's payment flows. Your role sits at the intersection of risk appetite, operational reality, and data-driven execution. You are responsible for translating risk strategy into concrete actions that improve accuracy, reduce financial exposure, and support sustainable business growth.

This role goes beyond analysis. You own risk controls, performance outcomes, and continuous improvement within your domain. Working closely with Machine Learning, Product, Compliance, and Operations, you help ensure that Trustly’s fraud detection framework remains precise, scalable, and aligned with regulatory and business expectations.

WHAT YOU'LL DO

* Own the configuration, performance, and continuous optimization of fraud models and rules, thresholds, and decision logic

* Be accountable for fraud KPIs and take active ownership of improving performance over time

* Conduct in-depth impact and root-cause analysis to support data-driven decision-making

* Translate operational insights and risk appetite into tangible detection and mitigation actions

* Collaborate closely with the Machine Learning team to align model outputs with fraud logic and improve overall prevention and detection performance

* Review, propose, and implement changes to thresholds, escalation logic, and risk controls

* Contribute to the drafting and refinement of fraud-related policies, procedures, and risk documentation

* Partner with stakeholders across Compliance, Product, and Operations to align mitigation strategies, process changes, and regulatory requirements

* Stay up to date on fraud trends, typologies, and industry best practices

WHO YOU ARE

* Several years of experience in fraud prevention, fraud analytics, or risk management within financial services or fintech

* Proven ability to own performance metrics and drive measurable improvements

* Strong understanding of fraud typologies, detection strategies, and risk control frameworks

* Highly analytical, with the ability to translate complex data into clear insights and actions

* Comfortable working at the intersection of rules-based controls and machine learning models

* Confident communicator, able to present insights to both technical and non-technical stakeholders

* Structured, accountable, and comfortable making risk-based trade-offs

* Curious and continuously learning, with a strong interest in improving detection precision

Shape your role and make an impact

At Trustly, seniority means ownership. As a Senior Fraud Data Analyst within Risk Precision, you are expected to challenge existing approaches, strengthen fraud controls, and help define what good looks like as fraud risks and detection techniques evolve. If you thrive in a fast-moving environment and want to actively influence how fraud prevention operates at scale, we’d love to hear from you.

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