Data Scientist, Payment Platform

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
Payments is Square's core product and the foundation for the growth of many other Square products. The mission of Square's Payments team is to make payments efficient, effective, and low-cost for Square - and to open the payments industry to Square's innovation.
As a data scientist on Square Payments Platform 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 Payments platform for Square and our third-party developers. You will 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 closely with product managers, engineers and cross functional teams including Risk and Finance teams to develop Square's global payments strategy.
You Will

• Partner with Square's product, engineering and operations teams to make data-driven decisions using a diverse set of tactics, including statistics, quantitative reasoning, and experimental design.
• Proactively identify gaps and opportunities in our processes. Design, run, and analyze experiments with the goal of optimizing the speed, cost, and acceptance of payments for our sellers.
• Independently research questions related to our core payments data and produce actionable insights for stakeholders.
• 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 payments data. Translate requests from internal and external partner teams into questions that can be rigorously answered with payments data.
• Communicate analysis and decisions to high-level stakeholders and executives in verbal, visual, and written media.
• Own, coordinate, and solve complex, cross-functional problems that extend beyond the traditional boundaries of product domains, analytics, and data science.
• Evangelize data best practices and be an advocate for a data-driven culture across Square.
• Lead and mentor others in data science on medium and long-term initiatives that span across product domains.

You Have

• 3+ 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.
• Experience in hypothesis testing, designing and analyzing A/B experiments, translating results into business decisions.
• Ability to manipulate, analyze, and interpret 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 with product partners.
• Experience in applying both data-backed heuristics and machine-learning techniques to solve practical product problems

Technologies We Use and Teach

• SQL
• Python (numpy, pandas, sklearn)
• Machine Learning (e.g. regression, ensemble methods, neural networks, etc.)
• Statistics (Bayesian methods, experimental design, causal inference)
• Google Cloud Platform: BigQuery, Dataflow, and Composer
• Airflow
• Looker
• Snowflake

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 an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We also consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.
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 .
Block will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.
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:
$142,000 - $213,000 USD
Zone B:
$134,900 - $202,300 USD
Zone C:
$127,800 - $191,600 USD
Zone D:
$120,700 - $181,100 USD
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.