Senior Machine Learning Engineer (Modeling)

Key Skills

Aartificial intelligence, AWS, Deep Learning, Google Cloud Platform (GCP), Java Programming, Machine learning techniques, MySQL, NumPy, Pandas, Python Programming, Snowflake, Tableau, TensorFlow, XGBoost

Job Description

Machine Learning is an integral part of how we design products, operate, and pursue Cash App’s mission to serve the unbanked as well as disrupt traditional financial institutions. Our massive scale and deep trove of transaction data create an endless number of opportunities to use artificial intelligence to better understand our customers and offer new products and experiences that can improve their lives. We are a highly creative group that prefers to solve problems from first principles; we move quickly, make incremental changes, and deploy to production every day. Check out our Machine Learning / AI blog here!

This role is part of our Cash App's ML team and will be deeply embedded within one of our product teams - here are the workstreams we're currently hiring for:

Search & Discovery

Cash App enables millions of people and businesses to pay and get paid with ease. On this team, you will build delightful experiences that help our customers find and discover people and things quickly and with trust - we aim to grow and strengthen the connections between people and businesses across the globe. Through your work, you will empower Cash App to personalize customers’ search and discovery experiences using AI/ML, to better understand our customers’ payment journeys, and help identify and execute on new opportunities for product improvement. You will employ a variety of modeling techniques on our comprehensive customer data and scale your solution to production by partnering closely with design, product, analytics, and engineering teams.

Recommendations + Incentives

We provide an ML-powered recommendation services platform that works for the entire gamut of our Product Abstractions and enables Cash to make creative and personalized customer experiences. Furthermore, our ML models used for incentives programs consistently provide value to the business and our customers by attracting and engaging more customers which directly contributes to the massive success of Cash.

Risk

You'll build machine learning models that detect fraudulent activity in real time and help keep our customers safe and secure. You will experiment with state-of-the-art algorithms to drive down false positives, collaborate on new product features to drive fraud losses down, use any and every dataset at your disposal (including 3rd party data) to engineer new features for risk models, verify customer documents using OCR, and use biometric and device signals to detect malicious logins and account takeovers.

Risk AI

We are a group aimed at developing deep learning based signals and learned representations for Risk ML models. Currently, Risk @ Cash ML models are predominantly based on tabular supervised tree-based models. Our team has the mandate to explore and implement alternatives based on SOTA neural network architectures and techniques. This is a particularly exciting time to join as you will be part of the first members of the team, and will have the opportunity to shape our roadmap.

Customer Support Automation

We aim to create better-than-human Customer Support Experiences. Cash App holds people’s money, and building customers’ trust is absolutely essential to our brand. Providing fast and reliable help whenever the customer needs it is a major component of building that trust. You will build models that anticipate customer issues and deliver proactive in-app suggestions, use NLP to contextualize inquiries and respond instantly with relevant content, develop prioritization algorithms that improve efficiency, and apply the latest research to automate conversations with customers.

Underwriting and Credit

Our mission is to redefine credit and liquidity through simple, fair, and accessible credit solutions that build financial health and resilience. This team builds and integrates ML solutions for evaluating customer cash flow risk including risk of default on credit obligations, risk of fraud & abuse of loans and other situations where Cash app advances funds or provides liquidity to customers. We support multiple products across 4+ workstreams in Cash. Through your work you will empower the team to understand the financial performance of origination cohorts, optimize our automated decisioning pipeline using AI/ML, and help identify new opportunities for growth in our customer base. You will experiment with various modeling techniques on our comprehensive customer data and see your solution through to production by partnering cross-functionally with finance, product, and engineering teams.

Technologies we use (and teach):

• Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.)
• MySQL, Snowflake, GCP/AWS and Tableau
• Java

Qualifications

You have:

• 5+ years experience with applied Machine Learning or Deep Learning
• A graduate degree in Computer Science, AI, ML, Applied Math, Stats, Physics, or a related technical field
• Worked with Product, Design, and Engineering to prioritize, scope, design, and deploy ML models
• A track record of providing mentorship and technical leadership
• An appreciation for the connection between the software you build and the experience it delivers to customers

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 $167,300 - USD $204,500
• Zone B: USD $158,900 - USD $194,300
• Zone C: USD $150,600 - USD $184,000
• Zone D: USD $142,200 - USD $173,800

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.

Benefits include the following:

• Healthcare coverage
• 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
• Learning and Development resources
• Paid Life insurance, AD&D. and disability benefits
• Perks such as WFH reimbursements and free access to caregiving, legal, and discounted resources

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.