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Cash App
Machine Learning Engineer, Commerce Fraud Risk
7 months ago | 659 views | Be the first one to apply

Machine Learning Engineer, Commerce Fraud Risk

Full-time
Remote

About the company

It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 47 million monthly active customers. We want to redefine the world’s relationship with money to make it more relatable, instantly available, and universally accessible. Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We’ve been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.

Job Summary

You will:

📍Develop, implement, and maintain machine learning models for fraud detection. 📍Analyze large datasets to identify patterns and trends related to fraudulent activities. 📍Collaborate with cross-functional teams to understand business needs and develop solutions to mitigate fraud risks. 📍Continuously monitor and evaluate the performance of machine learning models, making adjustments as necessary. 📍Stay up-to-date with the latest developments in machine learning and fraud detection, and incorporate new techniques and technologies into our processes as appropriate. 📍Prepare and present reports on model performance and fraud trends to stakeholders.

Qualifications

You have: 📍Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. A Master's degree is preferred. 📍5+ years of experience in machine learning, data analysis, or a related field. 📍Proven experience in fraud detection and risk management. 📍Strong knowledge of machine learning algorithms and data analysis techniques. 📍Proficiency in programming languages such as Python or Java. 📍Excellent problem-solving skills and attention to detail. 📍Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders.

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