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 the Identity workstream of our Trust organization and work closely with Identity product management as well as other cross-functional partners to deliver meaningful insights about our customers and our identity systems. Because our identity systems play such a critical role to the company and to expanding access to our users, a strong attention to detail and appreciation for storytelling with data is absolutely critical for this position.
As a Data Scientist you will:

• Partner directly with the Cash App Trust org, working closely with product, operations, engineers, legal and compliance, and machine learning teams
• Produce accurate and timely reports from complex datasets using SQL and scripting languages to deliver critical insights to the product team and other key stakeholders, both internal and external
• Approach problems from first principles, synthesizing large datasets into clear data visualizations and dashboards to tell compelling stories about customer behavior and product initiatives
• Build, monitor, and report on metrics that drive strategy and facilitate decision making for key business initiatives
• Demonstrate a sense of urgency, attention to detail, and excellent business judgment in all work
• Understand and interpret A/B experiments to incorporate the impact of changes we make into key performance indicators
• 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
• Effectively communicate your work with team leads and cross-functional stakeholders on a regular basis

Qualifications
You have:

• Previous exposure to or interest in areas like leadership reporting, anomaly detection, audit or regulatory data science
• A bachelor degree in statistics, data science, or similar STEM field with 5+ years of experience in a relevant role OR
• A graduate degree in statistics, data science, or similar STEM field with 2+ 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

Technologies we use and teach:

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

Qualifications
You have:

• Previous exposure to or interest in areas like leadership reporting, anomaly detection, audit or regulatory data science
• A bachelor degree in statistics, data science, or similar STEM field with 5+ years of experience in a relevant role OR
• A graduate degree in statistics, data science, or similar STEM field with 2+ 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

Technologies we use and teach:

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