Senior Data Scientist, Square for Retail

Company Description

Since we first opened our doors in 2009, the world of commerce has evolved immensely – and so has Square. After enabling anyone to take 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.

Job Description

Retailers have struggled too long with clunky, outdated and disconnected tools. Even as mammoth Retail and e-commerce forces threaten to disrupt smaller merchants, we are empowering those merchants with simple and elegant solutions to complex problems - like predictive analytics and fluid, omni-channel capabilities to meet customers wherever they are - to always make the sale. Square for Retail is one of Square’s three vertical Point of Sale solutions, focused on serving upmarket sellers. 

Square’s mission is economic empowerment, and Data Scientists support this by using data to understand and empathize with our customers, thereby enabling us to build a remarkable product experience. You and your fellow data science & analytics teammates on the Retail Analytics team are embedded within product and marketing sub-teams (“squads”), leveraging data engineering, analytics, statistics, and machine learning to empower data-driven decision making in the full life cycle of product development.

You will:

• Partner with the product, design, and marketing stakeholders to identify, prioritize, and answer the most important questions where analytics can have a material impact
• Apply a diverse set of tactics such as business intelligence, statistics, exploratory analysis, and machine learning; discerning where simple analytics solutions (e.g. a quick heuristic or visualization) are preferable to complex solutions (e.g. machine learning)
• Contribute to the data strategy of product engineering, influencing engineers to make well-informed architecture and design decisions that affect data at Square

Qualifications

You have:

• 5+ years of analytics experience, and a Bachelor’s degree or equivalent professional or academic experience
• Fluency in SQL, with experience exploring and understanding large, complex datasets & data systems
• Experience working with technical and non-technical partners, such as product managers and product marketing managers
• Experience with statistical and machine-learning techniques to solve practical business problems such as hypothesis testing, cross-selling, clustering user archetypes, and predicting churn
• Experience with a BI tool such as Looker or Tableau 

Even better:

• An advanced degree (M.S., PhD.) in Mathematics, Statistics, Computer Science, Physical Sciences, Economics, or a related technical field
• Experience with data warehouse design, development and best practices

Technologies we use and teach:

• SQL (Snowflake)
• Optimizely
• Airflow (ETL)
• Looker, Amplitude, Tableau
• Python (pandas, scikit-learn, etc.)

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 $152,100 - USD $185,900
Zone B: USD $144,500 - USD $176,700
Zone C: USD $136,900 - USD $167,300
Zone D: USD $129,300 - USD $158,100

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