Data Scientist, Trust and Risk

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 50+ 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.

The Role

The Data Science team at Cash App derives valuable insights from our unique datasets and turns those insights into actions that improve the experience for our customers and agents every day. In this role, you’ll be embedded with Risk Operations in our Risk organization and work closely with the Behavioral Insights Team as well as other cross-functional partners to deliver meaningful insights about our customers and our operational performance. Because the Behavioral Insights Team plays such a critical role in understanding our customers and our platform’s risk, a strong attention to detail and appreciation for storytelling with data is absolutely critical for this position.

You will

Partner directly with Risk Operations leads, working closely with other analysts, 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 leadership and other key stakeholders

Approach problems from first principles, using judgement to interpret requirements into technical solutions with clear data visualizations and dashboards that deliver actionable insights about customer behavior and operational performance

Build, monitor, and report on metrics that inform strategy and facilitate decision making for key business initiatives

Demonstrate a sense of urgency, attention to detail, and good 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

Effectively communicate your work with your team and cross-functional stakeholders on a regular basis

We’re Targeting

A Level 4 hire - typical experience for L4 would be something like BSc with 2-3 years; or an MSc or PhD with 1-2 years

A background in Statistics, Mathematics, Biostatistics, Economics or related quantitative field

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

Familiarity with experimentation techniques

Knowledge of cohort and funnel analyses and an understanding statistical concepts such as selection bias, probability distributions as well as conditional probabilities

Passion for understanding human behavior and improving operational processes that impact real customers

Technologies We Use and Teach

SQL, Snowflake, etc.

Python (Pandas, Numpy)

Tableau, Airflow, Looker, Mode, Prefect, dbt

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