Senior Data Scientist, Identity

Block

3h•$168,300 - $297,000•Remote

About The Position

The Identity Lifecycle team at Cash App ensures that our understanding of “who a customer is” stays accurate, compliant, and useful long after day one. In this role, you'll be embedded within the Trust: Identity & Controls organization and work closely with engineering, machine learning, risk, compliance, tax, and product partners to design and evolve the systems that manage customer identity over time—names, addresses, tax identities, KYC refreshes, and re‑verification when something changes or looks off. You'll use data and experimentation to shape policies and flows that keep identity data high‑quality while minimizing friction, and you'll directly influence how that identity state powers limits, eligibility, and access decisions across Cash App's ecosystem. Because identity is at the core of both customer trust and regulatory expectations, a strong sense of ownership, urgency, and appreciation for how these systems impact real customers' ability to use Cash App is absolutely critical in this position. Work from anywhere: This role can be performed from any location in the US with the flexibility to work from home

Requirements

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 5+ years of experience in a relevant role OR
A graduate degree in statistics, data science, or similar STEM field with 3+ 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

Responsibilities

Partner directly with the Cash App Trust Product 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