Risk Decision Scientist

Trustly

1d•Remote

About The Position

We are building an exciting new Risk Decision Science team at Trustly. Building on a strong foundation of risk, data science, and machine learning, we are expanding our capabilities with advanced analytical leaders who will shape strategy, own transaction decisioning, and partner with some of the largest companies in the world to manage complex bank risk, spanning from credit to fraud and abuse. As a Risk Decision Scientist, you will play a critical role in protecting Trustly and our merchants while balancing fraud prevention, credit performance, recovery outcomes, and customer experience. This is a highly strategic, analytical role where youâll identify systemic weaknesses, close gaps before fraudsters exploit them, and reduce friction for good customers. If this sounds like work you love, weâd love to talk.

Requirements

Minimum of 3+ years of experience in fraud or credit risk strategy within the fintech, e-commerce, or online payments industry.
Proficiency in SQL and Python, with a strong ability to work with large, complex datasets.
Bachelor's degree in Statistics or an equivalent quantitative field (e.g., economics, finance, engineering, exact sciences).
Demonstrated ability to use statistics and data science to solve complex, ambiguous problems and drive data-driven decisions.
Experience building and deploying rules or automated monitoring; familiarity with fraud patterns such as Account Takeover (ATO), stolen credentials, NSF/ACH risk, or knowledge of the U.S. banking ecosystem.
Able to turn complex analytics into simple, compelling stories for both technical and business audiences.
Prior experience in payments risk, ACH, bank transfers, or real-time payments ecosystems.
Strong product instincts - ability to influence roadmap, not just analyze data.
Prior experience in high-growth, ambiguous startup environments where structure needed to be built.

Nice To Haves

Experience with analytical visualization tools such as Tableau, QuickSight, Mode, or Looker is a plus.

Responsibilities

Own the end-to-end design, maintenance, and continuous optimization of risk strategy frameworks, decision policies, and rules to meet ambitious business and loss goals.
Use advanced analytics, SQL, Python, and statistical methods to solve complex problems, discover emerging risk trends, and inform high-impact decisions across the company.
Partner closely with Product, Engineering, Data Science, Finance, and Risk Operations to translate business needs into scalable, data-driven strategies and ensure successful execution.
Drive the development, maintenance, and refinement of risk strategy frameworks and complex rules to achieve ambitious business goals.
Detect anomalies and evolving fraud trends, write risk rules targeting fraud patterns, and closely monitor the solution performance.
Present strategies, findings, and recommendations to merchants and internal leadership, translating advanced ACH, risk, and fraud concepts into clear narratives that drive confidence, alignment, and action.
Master large volumes of data; extract and manipulate large datasets using standard tools such as SQL and Python.
Develop flexible performance dashboards and monitoring tools using platforms like Quicksight to provide clear, actionable insights to a variety of audiences and senior leaders.
Plan and measure experiments (A/B and multivariate tests) to analyze the incremental value of new intelligence feeds and transform test results into actionable business insights.