Senior Data Scientist - Risk & Fraud

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 Risk & Fraud organization and work closely with machine learning, product management as well as other cross-functional partners to drive strategy using a variety of data science techniques and own north star metric monitoring. Because our risk and fraud systems play such a critical role to the company and to protecting our users, a sense of urgency and appreciation for how our work impacts the customer experience is absolutely critical for this position.

As a Data Scientist you will:

• Partner directly with the Cash App Risk & Fraud org, working closely with machine learning, operations, engineers, product, legal, and compliance teams
• 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 and optimize our risk actions
• Work with engineers to log new, useful data sources to reflect our risk and 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

Requirements

You have:

• Previous exposure to or interest in areas like risk, fraud, statistical reporting methods, or regulatory data science
• A bachelor degree in statistics, data science, or similar STEM field with 4+ 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