Summary

Since Block's inception, our innovative and technology-forward approach to risk management and customer protection has been fundamental to how we invent and build financial products. The Risk team at Block continues this legacy through a sophisticated, technology and science-led approach to protecting our customers and their funds. Our interdisciplinary structure combines Product Development, Science teams (specializing in modeling, analytics, and data science), Operations and key partners including Legal Counsel and Policy, all working in concert to identify, assess, and solve complex risk challenges across access, fraud prevention and compliance.

In this role, you'll be embedded within the Trust & Risk Data Science team, focusing on Cash App users and collaborating with cross-functional teams to drive strategy through advanced statistical techniques. You'll be part of a broader ecosystem where multiple workstreams converge to declare, discover, and develop sophisticated product solutions to build lasting customer trust. Given that our trust and risk systems are fundamental to both company operations and user protection, this position requires a strong sense of urgency and deep appreciation for how our work directly impacts the customer experience across our entire product portfolio.

Work from anywhere: This role can be performed from any location in the United States. 

You Will

1. Analyze large datasets using SQL and scripting languages to surface actionable insights and opportunities to the product team and other key stakeholders
2. Approach problems from first principles, using a variety of statistical and mathematical modeling techniques to research and understand customer behavior
3. Design and analyze A/B experiments to evaluate the impact of changes and optimize the Access & Account Security product area
4. Work with engineers to log new, useful data sources to reflect our product features
5. Build, visualize and report on metrics that drive strategy and facilitate decision making for key business initiatives
6. 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
7. Effectively communicate your work with team leads and cross-functional stakeholders on a regular basis

We're Targeting

1. A Level 5 hire - typical experience for L5 would be something like BSc with 4-6 years; MSc with 2-5 years; or a PhD with 1-3 years
2. A background in Statistics, Mathematics, Biostatistics, Economics or related quantitative field
3. Previous exposure to or interest in areas like risk, fraud, statistical reporting methods, or regulatory data science
4. Advanced proficiency with scripting and data analysis programming languages (Python or R), SQL and data visualization tools
5. Deep familiarity with cohort and funnel analyses, a well-developed understanding statistical concepts such as selection bias, probability distributions, and conditional probabilities

Technologies We Use and Teach

1. SQL, Snowflake, etc.
2. Python (Pandas, Numpy)
3. Tableau, Airflow, Looker, Mode, Prefect

Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

To find a location’s zone designation, please refer to this resource. If a location of interest is not listed, please speak with a recruiter for additional information. 

Zone A:

$171,800—$257,600 USD

Zone B:

$163,200—$244,800 USD

Zone C:

$154,600—$232,000 USD

Zone D:

$146,000—$219,000 USD

Skills

• Data Structures
• Development
• Python
• Software Engineering
• SQL