Product Analytics Intern, Retail

  • New York, NY, USA
  • Intern
  • Current Square Employee?: Apply via go/jobs

Company Description

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.

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Retailers have struggled too long with clunky, outdated and disconnected tools.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. 

Based in New York City, Square for Retail is one of the newest and fastest-growing products at Square. We are a lean team, benefitting from (and contributing to) the resources of the larger organization while staying focused on solving Retail-specific challenges. We are relentlessly customer focused, and iterate quickly using a build-measure-learn approach.  

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

For this 12 week Summer 2020 internship, you will:

  • Work as a Product Analytics Intern embedded in the Square for Retail team, collaborating with Data Scientists/Product Analysts/Data Engineers across Square
  • Partner with the Retail product team to identify, prioritize, and answer the most important questions where analytics will have material impact
  • Use your experience in analytics tools and scientific rigor to produce actionable insights
  • Build visualizations that expose the health and performance of our products
  • Communicate key results to senior management in verbal, visual, and written media

Qualifications

You have:

  • Experience performing data analysis using SQL
  • Ability to understand complex business and data systems
  • Ability to clearly communicate complex results to technical and non-technical audiences
  • Versatility and willingness to learn new technologies on the job
  • Pursuing a degree in Statistics, Computer Science, Physical Sciences, Economics, or a related technical field

Even better:

  • Prior intern/job experience
  • An advanced degree (B.S., M.S., PhD.), preferably in Statistics, Computer Science, Physical Sciences, Economics, or a related technical field
  • Experience performing data analysis and/or machine learning using Python (pandas, scikit-learn, etc.) or R
  • Familiarity with BI tools like Looker or Tableau
  • Familiarity with Linux/OS X command line, version control software (Git), and general software development

Technologies we use and teach:

  • Python
  • Snowflake
  • Looker, Tableau

Additional Information

At Square, we value diversity and always treat all employees and job applicants based on merit, qualifications, competence, and talent. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. 

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