Senior Data Scientist, Cash for Business

Key Skills

Apache Airflow, Looker, NumPy, Pandas, Python Programming, R Programming, Snowflake, SQL, Tableau

Job Description

The Data Science team at Cash App derives valuable insights from our extremely unique datasets and turns those insights into actions that improve the experience for our customers every day. In this role, you’ll be embedded in our Commerce organization and work closely with product management as well as other cross-functional partners to drive product and business decisions with analytics insights, including both high-level strategy and low-level optimizations.

As shared in earnings reports, Commerce is one of the top three investments of Cash App. The mission of Cash for Business is to make Cash App the easiest way for anyone to become a mobile seller. We currently support millions of microsellers and mobile-native SMBs across the US. Cash for Business is the easiest way to get paid for selling goods or services by millions of people using Cash App.

You Will

• Analyze large datasets using SQL and scripting languages to surface actionable insights and opportunities to the product team and other key stakeholders
• Approach problems from first principles, using a variety of statistical and mathematical modeling techniques to research and understand customer behavior
• Design and analyze A/B experiments to evaluate the impact of changes we make to the product
• Work with engineers to log new, useful data sources as we build new product features
• Build, forecast, and report on metrics that drive strategy and facilitate decision making for key business initiatives
• Write code to effectively process, cleanse, and combine data sources in unique and useful ways, often resulting in curated ETL datasets that are easily used by the broader team
• Build and share data visualizations and self-serve dashboards for your partners
• Effectively communicate your work with team leads and cross-functional stakeholders on a regular basis

You Have

• 3+ years of data science experience partnering with product development
• Excellent communication skills, with the ability to present complex data insights to both technical and non-technical stakeholders
• Experience leading cross-functional projects and partnering with Product/Engineering/UX Research on strategy and prioritization
• Advanced proficiency with SQL and data visualization tools (e.g. Mode, Tableau, etc)
• Experience with scripting and data analysis programming languages, such as Python or R
• Strong background in statistical techniques and data science libraries
• Familiarity with standard machine learning concepts (e.g. regression/classification, clustering, offline/online model evaluation) and curiosity to learn more modern techniques as required
• Familiarity with data engineering best practices
• Experience working in the p2p payments, SMB facing or related fintech and financial services domains - not essential, but good to bring to the role

Technologies We Use and Teach

• SQL, Snowflake, etc.
• Python (Pandas, Numpy)
• Tableau, Airflow, Looker, Mode, Prefect

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. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We also consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.

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. Want to learn more about what we’re doing to build a workplace that is fair and square? Check out our I+D page.

Block will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.