Proven experience in a data science role with a focus on fraud detection, cybersecurity, or fin tech related domainsHave build machine learning models for Send Scam (Victim Identification) and Account Takeover (ATO)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, unsupervised learning methods, deep learning, and graph based solutionsDemonstrated ability to work collaboratively in cross-functional teams and effectively communicate complex technical concepts to non-technical stakeholders.A proactive, problem-solving mindset with a passion for protecting users from fraudulent activities.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 with mining into event logs to identify patterns and associationsYou 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 theseExperience 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.Additional Information
We’re people without borders — without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you’re passionate about learning new things and keen to join our mission, you’ll fit right in.
Also, 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.
And because we believe that diverse teams build better products, we’d especially love to hear from you if you’re from an under-represented demographic.
For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
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