Manager, Data Science and Machine Learning; Risk and Fraud

Manager, Data Science and Machine Learning (Risk and Fraud)

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.

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.

The Data team at Trustly is the backbone of our decision-making and product innovation. We are a global, multidisciplinary collective of Software Engineers, Data Engineers, Machine Learning Specialists, Scientists, and Analysts who believe that data is more than just rows and columns - it is the fuel for a more transparent financial ecosystem.

We operate at the intersection of high-scale engineering and deep financial intelligence. Our team processes millions of transactions in real time, turning complex Open Banking signals into seamless payment experiences. We pride ourselves on a culture of intellectual curiosity, technical excellence, and extreme ownership.

You will lead the team responsible for building and deploying the machine learning models at the heart of Trustly’s transaction decisioning—determining whether each transaction is approved and guaranteed. Your work will directly influence how we manage risk, prevent fraud, protect our customers, and deliver fast, reliable payment experiences at scale.

This is a hands-on leadership role. You will develop and ship production-ready models yourself while setting the technical direction for a team of data scientists and machine learning engineers. You will mentor and grow the team, establish strong modeling and experimentation practices, and take end-to-end ownership of its work—from roadmap and development through deployment, monitoring, and continuous improvement.

You will partner closely with Risk, Product, Engineering, and Finance to translate complex risk challenges into practical machine learning solutions and measurable business outcomes.

Build and Ship Models

• Build, validate, deploy, and continuously improve machine learning models for ACH return risk, fraud detection, and account takeover.
• Develop real-time, online, and offline features using transaction, account, device, network, and behavioral data.
• Design models that operate reliably in a low-latency, high-volume production environment.
• Design and analyze experiments to measure the impact of model and policy changes, including champion-challenger tests, holdouts, and staged rollouts.
• Quantify the impact of model changes across loss rates, approval rates, customer experience, merchant performance, and overall return on investment.
• Translate complex modeling results into clear insights and recommendations for nontechnical partners across Risk, Product, Finance, and the broader business.

• Mentor and develop a team of full-stack data scientists and machine learning engineers with strengths across both modeling and production engineering.
• Hire, assess, and level talent based on technical depth, business judgment, and the ability to build reliable production systems.
• Set a high bar for technical quality, execution, and accountability across the team.
• Take ownership of what the team delivers—what ships, when it ships, and how it performs in production.
• Own…