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

Square’s Account Management organization works with Square’s largest and most strategic merchants to grow and retain their businesses and to deliver insights to product teams. AM Automation builds automation and machine learning solutions to optimize the efficiency and impact of the Account Management team.

As a Data Scientist on the AM Automation team, you will use engineering, analytics, and machine learning to drive insights and decision-making for the Account Management organization. You will partner closely with strategy and business partners to design experimentation, and measure lift of different areas within the program. You will also deliver insights from activity and call transcript data across hundreds of thousands of interactions to derive scalable insights that will drive product development across Square.

You will:

  • Design and implement measurement methodologies to rigorously evaluate the revenue lift attributable to Account Management programs
  • 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
  • Partner closely with cross-functional teams spanning Finance, Strategy, Data Engineering, and Business
  • Deeply understand the Account Management 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

Qualifications

You have:

  • 3+ years of analytics and data science experience or equivalent
  • Experience with designing and executing A/B tests and familiarity with a range of lift and impact methodologies
  • Experience applying both statistical and machine-learning techniques to solve practical product problems such as predicting churn, LTV, cross-selling, and clustering user archetypes
  • 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
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