Data Scientist, Risk ML

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.

So we expanded into software and started building integrated, omnichannel solutions – to help sellers sell online, manage inventory, offer buy now, pay later functionality, 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.

The Role

We are looking for a Data Scientist to join our Risk Machine Learning team. This team is responsible for building processes to root out high-risk activity across the Square platform of products. This role will own pieces like managing top level Risk KPIs, establishing core operational metrics and making improvements through both complex analyses and machine learning solutions.

This role will call heavily on your analytical skills to identify and prevent fraud and credit risks and will leverage experimentation to promote risk effectiveness throughout Square. Data scientists at Block operate very cross functionally and you’ll plug into folks from product, engineering, operations, machine learning, policy and sales to influence Square's global Risk road map and processes. You will also make a direct impact on Square's priorities and banking initiatives (debit card and credit card businesses, loans, etc.) by building risk detection strategies, developing/tracking key success metrics, influencing partners through data and enabling growth of the business.

You Will

• Diagnose problems and develop compelling, data-driven recommendations


• Provide thought leadership in building and executing risk management strategies for new or existing product launches


• Design and analyze A/B experiments to measure the effectiveness of a Risk Management strategy


• Partner with Product, Engineering, Machine Learning Engineering, Policy and Operation teams to design solutions to business problems, influence product roadmaps, and develop new products/processes


• Use machine learning tools to develop data-driven solutions.


• Promote creative risk solutions through third-party evaluation and integration with a focus on improving the seller experience


• Effectively present your work with senior leaders and cross-functional stakeholders on a regular basis

You Have

• BS/BA in Statistics, Mathematics, Operations Research, Management Science, Computer Science, or a related technical field, OR BS/BA in Criminal Justice, Economics, Business, or a related business field


• 5+ years of relevant experience (or masters degree with 3+ years of experience)


• Familiarity with fraud/risk management, trust and safety, payments, or card business


• Proficiency with SQL, Python and Looker


• Hands-on work building/implementing machine learning models


• Experience driving data-driven solutions and executing their implementation


• Worked on ambiguous problems and unstructured questions


• A passion for Block's mission

Technologies We Use and Teach

• SQL, Snowflake, Databricks etc.


• Python (Pandas, Numpy)


• Airflow, Looker, Prefect

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:

$163,600 - $245,400 USD

Zone B:

$155,400 - $233,200 USD

Zone C:

$147,300 - $220,900 USD

Zone D:

$139,000 - $208,600 USD