Senior Data Scientist - Commerce

Company Description
It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 47 million monthly active customers. We want to redefine the world's relationship with money to make it more relatable, instantly available, and universally accessible.
Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We've been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.
Check out our locations, benefits, and more at cash.app/careers.
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 help deepen the integration of the Cash App and Afterpay ecosystems and focus on innovative products like Afterpay Plus. In addition to that standard technical and communication skills we target in a Data Science candidate, an understanding of consumer shopping experiences is a huge value add for candidates considering this role.

• 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

Qualifications

• Previous exposure to or interest in areas like anomaly detection or regulatory data science
• A bachelor degree in statistics, data science, or similar STEM field with 7+ years of experience in a relevant role OR
• A graduate degree in statistics, data science, or similar STEM field with 5+ years of experience in a relevant role
• Advanced proficiency with SQL and data visualization tools (e.g. Tableau, Looker, etc)
• Experience with scripting and data analysis programming languages, such as Python or R
• Gone deep with cohort and funnel analyses, a deep understanding statistical concepts such as selection bias, probability distributions, and conditional probabilities

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

Qualifications

• Previous exposure to or interest in areas like anomaly detection or regulatory data science
• A bachelor degree in statistics, data science, or similar STEM field with 7+ years of experience in a relevant role OR
• A graduate degree in statistics, data science, or similar STEM field with 5+ years of experience in a relevant role
• Advanced proficiency with SQL and data visualization tools (e.g. Tableau, Looker, etc)
• Experience with scripting and data analysis programming languages, such as Python or R
• Gone deep with cohort and funnel analyses, a deep understanding statistical concepts such as selection bias, probability distributions, and conditional probabilities

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