Data Science, Intern (Fall)
- Intern
Company Description
Job Description
The Point of Sale & Customers product org (aka, CPOS) is responsible for a portfolio of software offerings for small business owners, including the flagship Square Point of Sale, as well as add-on products that can be customized to each business owner's needs, such as Team Management and Gift Cards. As a member of the Point of Sale & Customers team, you will use engineering, analytics, and machine learning to empower data-driven decision-making in the full lifecycle of product development and bringing our products to market.
You will:
Partner with Square’s product teams to identify, prioritize, and answer the most important questions where analytics will have material impact
Use your experience in analytics tools and scientific rigor to produce actionable insights
Build visualizations that expose the health and performance of our products
Communicate key results and suggest recommendations to senior management in verbal, visual, and written media
Work closely with a product managers, product marketers, designers and engineers to evangelize data best practices and implement analytics solutions
Qualifications
You have:
- Pursuing a degree in Economics, Statistics, Computer Science, Mathematics, or related technical field
- Experience performing data analysis using Python (pandas, scikit-learn, etc.), R and/or SQL
- Ability to understand complex business and data systems
- Ability to clearly communicate complex results to technical and non-technical audiences
- Versatility and willingness to learn new technologies on the job
Even better:
- An advanced degree (M.S., PhD.), preferably in Statistics, Computer Science, Physical Sciences, Economics, or a related technical field
- Familiarity with Linux/OS X command line, version control software (git), and general software development
- Experience in programming or scripting to enable ETL development
- Familiarity with other data tools and databases such as Looker and Snowflake
- Experience using statistics and machine learning to solve complex business problems
- Previous industry experience or internships in product related analytics
- Independent research experience
Technologies we use and teach:
- Python
- Snowflake
- Statistics
- Amplitude, Looker
Additional Information
We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Square is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible.
Additionally, we consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
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
Square, Inc. (NYSE: SQ) builds tools to empower businesses and individuals to participate in the economy. Sellers use Square to reach buyers online and in person, manage their business, and access financing. Individuals use Cash App to spend, send, store, and invest money. And TIDAL is a global music and entertainment platform that expands Square's purpose of economic empowerment to artists. Square, Inc. has offices in the United States, Canada, Japan, Australia, Ireland, Spain, Norway, and the UK.