Data Scientist, Risk - Prevalence

Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.

The Role

This role will operate in the Compliance Data Science & Analytics team - chartered to put data at the center of the organization’s decisions. As we build out a bad activity prevalence sampling function, we need a data scientist with a strong academic background in statistics, fluency in the practical application of sampling methodologies, and the ability to enact organizational change through their findings. They will partner with compliance, risk, and product teams to identify and measure new and existing areas of unwanted behavior in order to inform controls and compliance monitoring.

You Will

• Spearhead the design, implementation, and analysis of bad activity prevalence sampling studies
• Leverage appropriate sampling methodologies tailored to measuring risk of money laundering and terms of service violations, ensuring studies provide an accurate picture of platform health
• Identify and mitigate potential biases and sampling errors to enhance the accuracy and reliability of findings
• Perform deep dive analysis into different customer segments and/or products to identify pockets of compliance risk and measure the effectiveness & impact of product controls
• Design and analyze experiments to assess the impact of compliance programs, leveraging A/B testing and causal inference methods to drive actionable insights
• Own executive-level reporting and metrics to measure risk and bad activity on the platform over time
• Collaborate with cross-functional teams to translate insights into strategic actions and program recommendations
• Communicate complex statistical concepts and results to both technical and non-technical audiences and influence teams to take action based on your recommendations

We're Targeting

• A Level 6 hire - typical experience for L6 would be something like BSc +7-10 years; MSc + 5-8 years; or a PhD + 3-5 years
• A background in Statistics, Mathematics, Biostatistics, Economics or related quantitative field
• Expert-level knowledge of sampling methodologies, with a proven ability to apply them in real-world scenarios and to identify and quantify sources of bias
• Expert-level abilities in SQL and data analysis/visualization tools (i.e. Tableau, Looker, Mode, Python libraries)
• Proficiency in scripting and data analysis programming languages, such as Python or R
• Deep experience using data to solve complex, ambiguous problems
• Vision to define problems and manage projects in a fast-­paced, evolving organization
• Track record of bringing data to life for any audience through written and verbal communication and data visualization
• Excellent communication and leadership abilities

Technologies We Use and Teach

• SQL 
• Python
• Looker/Tableau