Requirements:

Proven experience in a data science role, bonus if experience is related to fraud detection, anti-money laundering, or fintech related domains
Strong proficiency in machine learning frameworks and programming languages such as Python, R, or similar
Experience working with large datasets and data processing technologies (e.g., Hadoop, Spark, SQL)
Familiarity with anomaly detection, supervised and unsupervised learning methods, and real-time data analysis
Demonstrated ability to work collaboratively in cross-functional teams and effectively communicate complex technical concepts to non-technical stakeholders

What You'll Be Doing:

Lead the development and deployment of advanced machine learning models to enhance our detection of different criminal behaviours across different Wise markets
Analyze large volumes of data to identify trends, patterns, and anomalies associated with potential criminal behaviour
Design and implement experiments to evaluate the effectiveness of Fincrime detection systems and continuously improve their performance
Collaborate with analysts, compliance and engineers to translate business and compliance requirements into actionable data insights and solutions
Develop robust data pipelines, algorithms, and tools to support real-time detection and response to Fincrime activity
Stay informed about the latest advancements in data science and machine learning to ensure state-of-the-art capabilities in the Fincrime domain
Mentor and guide junior data scientists, fostering a culture of collaboration and continuous learning within the team

You have a solid knowledge of Python, and are able to make and justify design decisions in your code. You know how to use Git to collaborate with others (e.g. opening Pull Requests on GitHub) and are able to review code. Ability to read through code, especially Java. Demonstrable experience collaborating with engineering on services
You have experience working with compliance in assuring effectiveness of controls
You are familiar with a range of model types, and know when and why to use gradient boosting, neural networks, regression, autoencoders, clustering or a blend of these
Experience with statistical analysis and good presentation skills to drive insight into action
A strong product mindset with the ability to work independently in a cross-functional and cross-team environment
Good communication skills and ability to get the point across to non-technical individuals
Strong problem solving skills with the ability to help refine problem statements and figure out how to solve them

We’re people without borders — without judgement or prejudice, too. We want to work with the best people, no matter their background
If you’re passionate about learning new things and keen to join our mission, you’ll fit right in
Qualifications aren’t that important to us. If you’ve got great experience, and you’re great at articulating your thinking, we’d like to hear from you
Diverse teams build better products, so we’d especially love to hear from you if you’re from an under-represented demographic