Data Scientist

  • Full-time

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

We are looking for a Data Scientist to join our Risk Machine Learning & Decision Science team. You'll build processes to root out high-risk activity across the Square platform of products. You will also manage top level Risk KPIs, establish core operational metrics, and make improvements through machine learning solutions or deep dive analysis.

The Risk Data Scientist will leverage analytical skills to identify and remediate the payment risks. You will lead experimentations to promote Risk effectiveness throughout Square. You will partner with product, engineering, operations, policies and sales to influence Squares global Risk road map and processes. You will have a chance to own the key metrics, develop data pipelines, ETL as well as making direct impact to our key success metrics via building machine learning solutions, risk detection rule development and deployment.  

You Will

  • Diagnose problems and develop compelling, data-driven recommendations

  • Maintain, develop and manage various data pipelines and ETLs

  • Partner with Product, Engineering, and operation teams to design solutions to business problems, influence product roadmaps, and solution new products/processes

  • Have a chance to utilize machine learning tools to develop data driven solutions. 

  • Promote creative risk solutions through third-party evaluation and integration with a focus on improving the seller experience

  • Develop executive presentations for Squares leadership

Qualifications

  • A BS/BA in Statistics, Mathematics, Operations Research, Engineering, Computer Science, Economics, or a related quantitative/technical field

  • 6+ years of relevant experience (or masters and 4+ years)

  • Experience with SQL, Python and Looker

  • Experience with machine learning model development and deployment

  • Experience driving data-driven solutions and project-managing their implementation

  • Experience answering unstructured questions and managing projects and tasks to a conclusion

  • A passion for Square's mission

  • Experience or interest in risk, trust and safety, payments, or spam prevention

Additional Information

At Square, our purpose is to empower – within and outside of our walls. In order to build the best tools for the businesses and customers we support all over the world, we have to start at home with a workforce as diverse and empowered as our sellers. To this end, we take great care to evaluate all employees and job applicants equally, based on merit, competence, and qualifications. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage candidates from all backgrounds to apply. 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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