Job Description

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 and careful application of advanced techniques for mature ones

• Use data science techniques to use new data sources for modeling, making sense of messy datasets and bringing clarity to decisions

• Support team members in ad-hoc and scheduled updates to existing models, and help troubleshoot issues in a real-time production environment

• Work with product engineers within the product teams and broader Block/Square platform teams

Qualifications

You Have:

• Minimum of 3 years of hands-on data analysis experience in full-time professional, data-heavy, and machine learning focused role

• 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

• Strong quantitative intuition and data visualization skills for ad-hoc and exploratory analysis

• The versatility to communicate clearly with both technical and non-technical audiences

• Experience with tree based models and gradient boosting is helpful but not required