Anti-Financial Crime Modelling Analyst

About us :

Luno is the crypto investment app you can rely on, enabling you to buy, store and explore crypto securely. We’re committed to putting the power of cryptocurrency in everyone's hands sensibly and responsibly.

Since 2013, we’ve helped millions of people around the world invest safely in crypto. We do this by cutting through the hype and supporting customers at every step of the way. All products and cryptocurrencies on our platform must first meet stringent legal, risk and technical security standards.

Transparency is key for us. Luno stores all crypto on a 1 : 1 basis and we have rigorous processes in place so you can be confident your investment is secure. We’re available in more than 40 countries around the world and we work closely with respective regulators in all of these markets to be fully compliant, as we believe this is the best way to help everyone, everywhere, invest safely.

About the team :

The Analytics team forms part of the broader Anti-Financial Crime division and you will report to the Analytics Manager who is based in Cape Town. Our vision is to become the best Anti-Financial Crime team in the industry, globally!

The role in a nutshell :

As an Anti-Financial Crime Modelling Analyst, you’ll be focusing on building and empowering the Anti-Financial Crime Analytics team with the Analytics Manager. You’ll also be working closely with other Anti-Financial Crime team members. You’ll be facilitating cross-team projects, helping shape our platform to reward genuine behaviour and identify and respond to unusual or suspected behaviour, whilst contributing to our growth plan.

Your mission will be :

• Develop, monitor and refine AML / Fraud models and rules to minimise false positives and surface high-risk behaviour, including feature engineering, tuning, drift monitoring, and effectiveness testing (precision / recall, PR curves, shadow / A-B tests)
• Partner with Anti-Fraud to design pro-active fraud detection and smarter friction (In-house fraud monitoring rules and ML-driven alternatives), balancing risk vs customer experience.
• Ship production-ready analytics in Databricks (Python / PySpark, Jobs / Workflows); collaborate with data platform development to ensure data readiness and reliability.
• Document and govern changes (model docs, audit trail, playbooks)
• Raise the bar on quality (unit tests for logic, code reviews, reproducible notebooks, clear acceptance criteria) and contribute to our backlog burn-down.

A little about you :

Benefits :

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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