Machine Learning Engineer, Banking & Square Financial Services

Company Description

Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.

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

• 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

• 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

Additional Information

Block takes a market-based approach to pay, and pay may vary depending on your location. U.S locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

Zone A: USD $148,700 - USD $223,100
Zone B: USD $141,300 - USD $211,900
Zone C: USD $133,800 - USD $200,800
Zone D: USD $126,400 - USD $189,600

To find a location’s zone designation, please refer to this resource. If a location of interest is not listed, please speak with a recruiter for additional information. 

Full-time employee benefits include the following:

• Healthcare coverage (Medical, Vision and Dental insurance)
• Health Savings Account and Flexible Spending Account
• Retirement Plans including company match 
• Employee Stock Purchase Program
• Wellness programs, including access to mental health, 1:1 financial planners, and a monthly wellness allowance 
• Paid parental and caregiving leave
• Paid time off (including 12 paid holidays)
• Paid sick leave (1 hour per 26 hours worked (max 80 hours per calendar year to the extent legally permissible) for non-exempt employees and covered by our Flexible Time Off policy for exempt employees) 
• Learning and Development resources
• Paid Life insurance, AD&D, and disability benefits 

These benefits are further detailed in Block's policies. This role is also eligible to participate in Block's equity plan subject to the terms of the applicable plans and policies, and may be eligible for a sign-on bonus. Sales roles may be eligible to participate in a commission plan subjec