Machine Learning Engineer (Modeling), Square Financial Services

The Role
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

We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, based solely on the core competencies required of the role at hand, and without regard to any legally protected class. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build an inclusive workplace? Check out our Inclusion & Diversity page
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 subject to the terms of the applicable plans and policies. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.
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.
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.
Zone A:
$228,700 - $343,100 USD
Zone B:
$217,300 - $325,900 USD
Zone C:
$205,900 - $308,900 USD
Zone D:
$194,500 - $291,700 USD
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. Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning are just some of our offering. Check out our other benefits at Block.
Block, Inc. (NYSE: XYZ) builds technology to increase access to the global economy. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we're helping build a financial system that is open to everyone.