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.
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
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
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:
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.
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, without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other 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 a workplace that is fair and square? Check out our I+D page.
Additionally, we consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
We’ve noticed a rise in recruiting impersonations across the industry, where individuals are sending fake job offer emails. Contact from any of our recruiters or employees will always come from an email address ending with @block.xyz, @squareup.com, @tidal.com, or @afterpay.com, @clearpay.co.uk.
Block, Inc. (NYSE: SQ) is a global technology company with a focus on financial services. Made up of Square, Cash App, Spiral, TIDAL, and TBD, we build tools to help more people access the economy. Square helps sellers run and grow their businesses with its integrated ecosystem of commerce solutions, business software, and banking services. With Cash App, anyone can easily send, spend, or invest their money in stocks or Bitcoin. Spiral (formerly Square Crypto) builds and funds free, open-source Bitcoin projects. Artists use TIDAL to help them succeed as entrepreneurs and connect more deeply with fans. TBD is building an open developer platform to make it easier to access Bitcoin and other blockchain technologies without having to go through an institution.
While there is no specific deadline to apply for this role, on average, U.S. open roles are posted for 70 days before being filled by a successful candidate.
Yearly based
Oakland, CA, United States