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 worldās 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. Weāve 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:
šDevelop, implement, and maintain machine learning models for fraud detection. šAnalyze large datasets to identify patterns and trends related to fraudulent activities. šCollaborate with cross-functional teams to understand business needs and develop solutions to mitigate fraud risks. šContinuously monitor and evaluate the performance of machine learning models, making adjustments as necessary. šStay up-to-date with the latest developments in machine learning and fraud detection, and incorporate new techniques and technologies into our processes as appropriate. šPrepare and present reports on model performance and fraud trends to stakeholders.
Qualifications
You have: šBachelor's degree in Computer Science, Statistics, Mathematics, or a related field. A Master's degree is preferred. š5+ years of experience in machine learning, data analysis, or a related field. šProven experience in fraud detection and risk management. šStrong knowledge of machine learning algorithms and data analysis techniques. šProficiency in programming languages such as Python or Java. šExcellent problem-solving skills and attention to detail. šStrong communication skills, with the ability to explain complex concepts to non-technical stakeholders.
