Data Scientist, Growth

  • Atlanta, GA, USA
  • Employees can work remotely
  • Full-time
  • Position open to remote: Yes

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. Square made credit card payments possible for all by turning a mobile phone into a credit card reader. Since then Square has been building an entire business toolkit of both hardware and software products including Square Capital, Square Terminal, Square Payroll, and more. 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

As a Data Scientist within the Growth Data Science team, you will lead projects that help with Square’s growth. The team exists to surface the right messages to the right sellers at the right time across all our go-to-market channels (web app, in-app, notifications, sms, email, mail, etc) as well as product surfaces. We provide sellers with remarkable experiences using machine learning to power the best product/feature/content recommendations.

Our algorithms derive value from our unique, rich, and rapidly growing data. We partner with business, product, operations and engineering teams to drive better decisions, automated and human, using sophisticated modeling and machine learning. We’re a passionate team of hackers, engineers, statisticians, and optimizers who are resourceful in distilling questions, wrangling data, and driving impactful business decisions.

You will:

  • Lead and drive cross functional data science projects from beginning to end: build relationships with partner teams, frame and structure questions, collect and analyze data

  • Apply descriptive and predictive analytics to help drive insights and business decisions

  • Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning to research and produce insights

  •  Deeply understand the Acquisition Marketing data ecosystem, and apply data science to support the growth of the organization

  •  Communicate analysis and decisions to high-level stakeholders and executives in verbal, visual, and written formats

  • Collaborate with business leaders, subject matter experts, and decision makers to develop success criteria and optimize new products, features, policies, and models

Qualifications

You have:

  •  3+ years of analytics and data science experience or equivalent

  •  Experience applying both statistical and machine-learning techniques to solve practical product problems

  • Strong written and verbal communication skills and ability to build relationships and influence across the organization

  •  Proven ability to facilitate cross-functional projects that depend on the contributions of others in a variety of disciplines

  •  Fluency with data warehouse design practices, analytics, and visualization technologies (we use SQL, Looker, and Python)

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. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to assistance(at)squareup.com. We will treat your request as confidentially as possible. In your email, please include your name and preferred method of contact, and we will respond as soon as possible.

Perks

At Square, we want you to be well and thrive. Our global benefits package includes:
  • Healthcare coverage
  • Retirement Plans
  • Employee Stock Purchase Program
  • Wellness perks
  • Paid parental leave
  • Paid time off
  • Learning and Development resources