Data Scientist, Customer Identity & Access Management

Company Description

Square builds common business tools in unconventional ways so more people can start, run, and grow their businesses. When Square started, it was difficult and expensive (or just plain impossible) for some businesses to take credit cards. 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 through Afterpay, 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. We’re working to find new and better ways to help businesses succeed on their own terms—and we’re looking for people like you to help shape tomorrow at Square.

Job Description

Our Customer Identity and Access Management (CIAM) team sits within the Commerce Platform organization and is responsible for creating remarkable products and experiences for our sellers, developers, buyers, and more. We’re responsible for creating a shared platform for user accounts, access management, and policy enforcement. Growing Upmarket is a critical priority for Square, and this is a pivotal role to enable us to succeed. The team is responsible for foundational data models, APIs, intuitive UX for various actors to set up and manage their accounts within Square, and tooling to enable internal stakeholders to support our sellers better. This includes ownership of standards-based authentication flows and session management across the Square ecosystem for all platforms (iOS, Android, and web).

As a Data Scientist on Square Commerce Platform's centralized data science team, you will leverage analytics, engineering, and machine learning to empower data-driven decision making, with the aim of ensuring a reliable, scalable, and secure platform for Square and our sellers. You will partner closely with product managers, engineers, and other data scientists to identify gaps and opportunities in our current processes, design business, and product metrics, lead experimentation initiatives to improve those metrics, and develop automated solutions to help partner teams understand the health of our core business. 

You will:

• Partner primarily with CIAM product, engineering, and design teams to make data-driven decisions using a diverse set of tactics, including statistics, quantitative reasoning, and experimental design. You will also work closely with Risk, Payments, and other cross-functional teams. 
• Proactively identify gaps and opportunities in our processes. Design and analyze experiments with the goal of increasing Square’s bottom line and ensuring Sellers' accounts are safe.
• Build ETL pipelines, dashboards, and machine learning models that enable monitoring of the health and performance of our core business.
• Be the subject matter expert on CIAM data. Translate requests from internal and external partner teams into questions that can be rigorously answered with data.
• Communicate analysis and decisions to high-level stakeholders and executives in verbal, visual, and written media.
• Evangelize data best practices and be an advocate for a data-driven culture across Square.

Qualifications

You have: 

• 2+ years of industry experience in data science, product analytics, or machine learning-focused roles.
• Proficiency in SQL and Python, as well as working knowledge in the application of statistical and modeling techniques; willingness to learn new technologies on the job.
• Proven track record of adding business value using data.
• A strong Data Engineering background. Ability to ingest and analyze large data sources independently.
• Proficiency in at least one visualization tool (we primarily use Looker).
• Strong written and verbal communication skills and the ability to build strong relationships and influence product part