Machine Learning Engineer

As a Machine Learning Engineer on the Banking & SFS team, you will support fellow Data Scientists and Modelers in building and deploying machine learning models that support our banking and lending business. Square Banking includes some of the fastest growing products that have a material contribution to Block’s business. This is a product focused modeling role in which the work has immediate customer and financial impact.

You’ll have the chance to engage with a diverse range of team members including product, data engineering, operations, and individuals in investor relations & capital markets. We are looking for “full stack” contributors that can engage across the spectrum from business strategy discussions to statistics and implementation details.

You Will

• Implement and deploy modeling approaches to grow new products, as well as careful application of advanced techniques for mature ones
• Use data science techniques to leverage new data sources for modeling, making sense of messy datasets and bringing clarity to business decisions
• Lead complex ML Operations and Infrastructure initiatives that advance our modeling capabilities (e.g. scaling data ingestion, enabling more complex neural networks, etc)
• Support team members in ad-hoc and scheduled updates to existing models, and help troubleshoot issues in a real-time production environment
• Work closely with product engineers within the product teams and broader Block/Square platform teams

You Have

• Minimum of 3 years of hands-on data analysis experience in full-time professional, data-heavy, and machine learning focused role
• An advanced degree (PhD preferred) in computer science or a similar technical field
• Strong engineering and coding skills, with the ability to write production code. Proficiency in Python required, Java and/or other languages optional
• Experience with Google Cloud Platform, Amazon Web Services or other cloud computing platforms
• Experience developing and deploying machine learning and statistical models
• Data visualization skills for ad-hoc and exploratory analysis
• Experience working with both technical and non-technical audiences
• A willingness to solve problems using whichever tool is most appropriate for the situation, balancing multiple business and technical constraints
• Experience with tree based models and gradient boosting is helpful but not required