Since we opened our doors in 2009, the world of commerce has evolved immensely, and so has Square. After enabling anyone to take payments and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldn’t work together.
To solve this problem, we expanded into software and built integrated solutions to help sellers sell online, manage inventory, book appointments, engage loyal buyers, and hire and pay staff. Across it all, we’ve embedded financial services tools at the point of sale, so merchants can access a business loan and manage their cash flow in one place. Afterpay furthers our goal to provide omnichannel tools that unlock meaningful value and growth, enabling sellers to capture the next generation shopper, increase order sizes, and compete at a larger scale.
Today, we are a partner to sellers of all sizes – large, enterprise-scale businesses with complex operations, sellers just starting, as well as merchants who began selling with Square and have grown larger over time. As our sellers grow, so do our solutions. There is a massive opportunity in front of us. We’re building a significant, meaningful, and lasting business, and we are helping sellers worldwide do the same.
As a Machine Learning Modeler within the Risk Machine Learning and Decision Science team, you work on projects that enable a software driven, machine learning centric view on all money movement and every transaction within the rapidly growing Square ecosystem. This touches on actively maximizing the trade off of revenue growth and risk using artificial intelligence. The machine learning driven software that we release interacts with every transaction and money movement within our seller ecosystem - a profound degree of scale and impact. Such machine learning techniques touch on transfer learning, reinforcement learning, decision theory, deep learning sequence modeling, natural language processing, and optimization theory. In addition, we also strive to provide our sellers, through seller facing products, with transparency around why our machine learning made a particular decision. This touches on algorithms in the relatively new space of explainable artificial intelligence.
We are seeking a highly motivated and experienced Staff Machine Learning Modeler to join the Payment credit risk team. The successful candidate will lead the development and maintenance of predictive models that drive our credit risk strategies, and will work closely with stakeholders to ensure optimal credit risk management. The successful candidate will play a crucial role in developing and executing the team's roadmap and long term strategy for payment credit risk modeling, and will be responsible for hands-on building and maintaining predictive ML models that drive our credit risk strategies. You are not only an executor but also a visionary leader to drive business and team growth.
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 $202,500 - USD $247,500
Zone B: USD $192,400 - USD $235,200
Zone C: USD $182,300 - USD $222,800
Zone D: USD $172,200 - USD $210,400
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.
US and Canada EEOC Statement
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, 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, and always assess candidates on an individualized basis.