Staff Machine Learning Engineer (Modelling), Risk

Machine Learning is an integral part of how we at Cash App design products, operate, and pursue our mission to serve the unbanked as well as disrupt traditional financial institutions. Our massive scale and deep trove of transaction data create an endless number of opportunities to use ML and AI methods to better understand our customers and offer new products and experiences that can improve their lives. We are a highly creative group that prefers to solve problems from first principles; we move quickly, make incremental changes, and deploy to production every day. As part of the Risk ML team, you will build machine learning models that detect fraudulent activity in real time and help keep our customers safe and secure. You will experiment with state-of-the-art algorithms to drive down false positives, collaborate on new product features to drive fraud losses down, use any and every dataset at your disposal to analyze emerging fraud patterns, engineer new features for risk models, and deploy robust models to take action on bad activity in real time. This role can work remotely from anywhere in Australia or New Zealand, or from our offices in Melbourne, Sydney and Auckland. You Will

Be responsible for building machine learning models to detect and act against fraudulent activity, as well as researching emerging fraud patterns, and leading and participating in cross-functional initiatives to tackle problems. Collaborate cross-functionally with our engineering, product, and operations teams located across Australia and the United States (particularly Melbourne and San Francisco) to keep our customers and their money safe. Work closely with the ML Engineering teams who build the systems that allow our models to operate at scale and in real time. Contribute to the growth of our modelling capabilities through mentoring and supporting fellow modellers. Exercise a high level of autonomy and responsibility, owning your solutions from design through to operation. You Have

Bachelor's degree in a quantitative field such as Mathematics/Statistics/Physics or Machine Learning. Masters or PhD preferred. 5+ years of experience in machine learning, artificial intelligence, or a related field. Strong knowledge of machine learning algorithms and data analysis techniques. Excellent problem-solving skills and attention to detail. Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders. Technologies We Use and Teach

Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.) MySQL, Snowflake, Tableau, Mode. GCP/AWS. Every benefit we offer is designed with one goal: empowering you to do the best work of your career while building the life you want. Check out benefits at Block.

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