Data Scientist, Square Appointments

  • San Francisco, CA, 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

The Appointments team at Square is focused on creating purpose-built tools for businesses that sell their time (think: hair stylists at salons, trainers at gyms, lawyers, contractors). On this team, we're building brand new products on top of Square's revolutionary payments platform to make the lives of these professionals easier and more productive, and the experience for their customers more modern and seamless. 

As a member of the Square Appointments data team, you will use engineering, analytics, and machine learning to empower data-driven decisions in the full life cycle of product development and bringing our products to market. You will run experimentation and growth plans, develop solutions to personalize product experiences, provide insights to our sellers about their business, and guide strategic decisions with data.

You will:

  • Partner directly with the product team to make data decisions across the organization by applying descriptive and predictive analytics where it will have a material impact
  • Design A/B experiments to evaluate the impact of changes we make to the product
  • Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning to research and produce insights
  • Coordinate and solve complex projects that extend beyond the traditional boundaries of product domains, analytics, and data science
  • Work with engineers to log new, useful data sources as we build new product features

Qualifications

You have:

  • 3+ years of analytics and data science experience or equivalent
  • Experience leading projects that depend on the contributions of others in multiple disciplines
  • Experience applying both statistical and machine-learning techniques to solve practical product problems such as predicting churn, LTV, cross-selling, and clustering user archetypes
  • Fluency with data warehouse design practices, analytics, and visualization technologies (we use SQL, Looker, and Python)

Nice to have: 

  • M.S in a quantitative field (mathematics, statistics, or similar STEM field)
  • Experience working on business and product projects focused on growth and retention
  • Familiarity with Marketing analytics and experimentation

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