Senior Machine Learning Engineer (Modeling), Risk
- Toronto, ON, Canada
- Employees can work remotely
Since we first opened our doors in 2009, the world of commerce has evolved immensely – and so has Square. After enabling anyone to make a payment and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldn’t work together. So we expanded into software and started building integrated, omnichannel solutions – to help sellers sell online, manage inventory, run a busy kitchen, book appointments, engage loyal buyers, and hire and pay staff. And 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 all in one place.
Today, we’re a partner to sellers of all sizes – large, enterprise-scale businesses with complex commerce operations, sellers just starting out, as well as merchants who began selling with Square and have grown larger over time. As our sellers scale, so do our solutions. We all grow together.
There is a massive opportunity in front of us. We’re building a business that is big, meaningful, and lasting. And we are helping sellers around the world do the same.
As a Machine Learning Engineer within the Risk Machine Learning 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 reinforcement learning, decision theory, deep learning sequence modeling, 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.
Our algorithms derive value from our unique and rich data from our entire product portfolio within our rapidly growing seller ecosystem. We partner with business, product, operations and engineering teams to drive optimal decision making systems using sophisticated modeling and machine learning. We’re a passionate team of entrepreneurs, scientists, and engineers who are shipping machine learning software that actively actively manages Square’s view on each transaction as it pertains to our revenue growth and risk.
Build and deploy machine learning/deep learning models that detect risk (credit or fraud) activity in real time across our Seller’s ecosystem consisting of payments, banking and debit card products.
You will leverage experimentation mindset along with state-of-the-art algorithms to drive down false positives, collaborate on new product features to drive losses down and explore new datasets (including 3rd party data) to engineer new features for risk models.
Collaborate with business leaders, subject matter experts, and decision makers to develop success criteria and optimize new products, features, policies, and models
An advanced degree (M.S., PhD.), preferably in Computer Science, Engineering, Statistics, Physics, Mathematics, or a related technical field.
PhD. plus 2 years (or Master plus 5 years) industry working experience on applied Machine learning or Deep learning
A strong track record of performing machine learning model development using Python (numpy, pandas, tensorflow, pytorch, scikit-learn, etc.) and SQL/NoSQL interaction patterns.
Expert level knowledge of modern techniques in machine learning and deep learning, e.g., transformer network architectures, with an orientation to maximizing such algorithms in a large scale production setting. Reinforcement learning experience is a plus for developing optimal control policies
Familiarity with Linux/OS X command line, version control software (git), and general software development principles with a machine learning software development life-cycle orientation.
Machine learning strategic sequencing of methodological and software improvements to work back from maximizing core metrics associated with optimizing the business.
The ability to clearly communicate complex results to technical and non-technical audiences and stakeholders (PMs, Operations, Engineers).
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.
We want you to be well and thrive. Our global benefits package includes:
- Healthcare coverage
- Retirement Plans
- Employee Stock Purchase Program
- Wellness perks
- Paid parental leave
- Paid time off
- Learning and Development resources
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.