Product Analyst, Retail
- New York, NY
We believe everyone should be able to participate and thrive in the economy. So we’re building tools that make commerce easier and more accessible to all. We started with a little white credit card reader but haven’t stopped there. Our new reader helps our sellers accept chip cards and NFC payments, and our Cash app lets people pay each other back instantly. We’re empowering the independent electrician to send invoices, setting up the favorite food truck with a delivery option, helping the ice cream shop pay its employees, and giving the burgeoning coffee chain capital for a second, third, and fourth location. Let’s shorten the distance between having an idea and making a living from it. We’re here to help sellers of all sizes start, run, and grow their business—and helping them grow their business is good business for everyone.
Your local retail store owner has struggled too long with clunky, outdated and disconnected tools. While massive Retail and E-tail forces are using their scale to win themselves buyers, we are using our scale to level the playing field for small-to-midsize businesses. We’re building them streamlined and elegant solutions to complex problems like advanced inventory and order management, predictive analytics to keep their businesses running smoothly and fluid omni-channel capabilities so they can meet their buyers wherever they are. We on the Square for Retail team believe the brightest future of Retail is in the customer connection - and we’re betting on small businesses to win.
Product Analysts at Square are embedded within product teams and leverage engineering, analytics, and machine learning to empower data-driven decision making in the full life cycle of product development. Square’s mission is economic empowerment, and our team supports this by using data to understand and empathize with our customers, thereby enabling us to build a remarkable product experience. For more insight into what we do, check out this blog post.
As a Product Analyst on the Square for Retail team, you will:
Partner with the product stakeholders to identify, prioritize, and answer the most important questions where analytics will have a material impact: using your experience in analytics tools and scientific rigor to produce actionable insights
Provide comprehensive day-to-day analytics support to partner teams, developing tools and resources to empower data access and self-service so your advanced expertise can be leveraged where it is most impactful
Build visualizations that expose the health and performance of our products, and proactively investigate & communicate the key drivers of the business
Discern where simple analytics solutions (e.g. a quick visualization) are preferable to complex solutions (i.e. machine learning)
Communicate analysis and decisions to high-level stakeholders and executives in verbal, visual, and written media
Contribute to the data strategy of product engineering, influencing engineers to make well-informed architecture and design decisions that affect data at Square
Lead and mentor others in Product Analytics on medium and long-term cross-functional initiatives that span product domains
2+ years of analytics experience or equivalent
Experience performing data analysis using SQL, and familiarity with a BI tool such as Looker or Tableau (we use Looker)
Very strong communication skills: ability to clearly communicate complex results to technical and non-technical audiences in verbal, visual, and written media
Proven ability to lead cross-functional projects that depend on the contributions of others in a variety of disciplines
Ability to understand complex business and data systems; versatility and willingness to learn new technologies on the job
An advanced degree (B.S., M.S., PhD.) in Mathematics, Statistics, Computer Science, Physical Sciences, Economics, or a related technical field
Familiarity with data warehouse design, development and best practices
Experience performing data analysis and/or machine learning using Python (pandas, scikit-learn, etc.) or R
Familiarity with Linux/OS X command line, version control software (Git), and general software development
Experience in applying both data-backed heuristics and machine-learning techniques to solve practical product problems such as predicting churn, cross selling, clustering user archetypes, and more