Data Scientist

Ibu5rash 400x400 Square | San Francisco


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, and helping the ice cream shop pay its employees. And, with Square Capital, we have extended over $1 billion in funding to our sellers, helping them manage their cashflow and making it easy to invest in and grow their business. Let’s shorten the distance between having an idea and making a living from it. And make it easier for customers to shop and pay at their favorite businesses. 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

As a Data Scientist at Square, you will lead projects that derive value from our unique, rich, and rapidly growing data. We’re a passionate team of hackers, statisticians, and optimizers who are resourceful in distilling questions, wrangling data, and driving decisions. 


As a Data Scientist at Square, you will work with one of our teams:


Cash:

You will lead the development of fraud detection algorithms and systems that protect Square Cash and its customers from fraud and financial loss. You will partner with Square Cash’s product and operations teams to identify, prioritize, and answer the most important questions where analytics and modeling will have a material impact in preventing fraud and financial loss.


Risk:

You will lead the development of fraud detection algorithms and systems that protect Square and its customers from fraud and financial loss. You will partner with Square’s Risk team to identify, prioritize, and solve complex problems where analytics and data science will have a significant impact.


You will: 

  • Drive cross functional analytics projects from beginning to end: build relationships with partner teams, frame and structure questions, collect and analyze data, as well as summarize and present key insights in support of decision making

  • Work with engineers to evangelize data best practices and implement analytics solutions

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

  • Use your experience in analytics tools and scientific rigor to produce actionable insights

  • Communicate key results to senior management in verbal, visual, and written media

  • Develop risk models that enable financial services for our customers

  • Help build the next generation of data products at Square

Qualifications

You have:


  • An advanced degree (M.S., PhD.), preferably in Statistics, Computer Science, Physical Sciences, Economics, or a related technical field
  • A consistent track record of performing data analysis using Python (numpy, pandas, scikit-learn, etc.) and SQL
  • Experience using statistics and machine learning to solve complex business problems

  • The versatility and willingness to learn new technologies on the job

  • The ability to clearly communicate complex results to technical and non-technical audiences

Even Better:
  • 2+ years industry experience in data-science or analytics
  • Familiarity with other data tools such as Hive, Vertica, Tableau, Ruby

  • Familiarity with Linux/OS X command line, version control software (git), and general software development
Technologies we use and teach:
  • Python (numpy, pandas, sklearn) & R
  • MySQL, Vertica, Hive, Redshift

  • Machine Learning (e.g. regression, ensemble methods, etc.)

  • Statistics (Bayesian methods, experimental design, causal inference)

  • 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. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
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