Senior Decision Scientist, Risk

Block • San Francisco Bay Area, CA

18h • Remote

About The Position

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 We're looking for a Decision Scientist to develop, implement, and own automatic risk decisions designed to mitigate Block's regulatory risk within the Transaction Monitoring and Disputes organization. In this role, you'll apply data-driven techniques to identify opportunities, design risk policies, and directly impact how Block manages risk across our major brands. You will be responsible for building analytical frameworks, evaluating heuristic and ML-driven decisions, and defining scalable, defensible risk policies. Your work will directly impact Block customers and escalate to our Risk operations teams for further review. You'll partner closely with Compliance, Risk, Machine Learning, Operations, Engineering, Legal, and Product stakeholders to balance regulatory requirements, loss mitigation, and customer experience. Work from anywhere: This role can be performed from any location in the US with the flexibility to work from home

Requirements

• Advanced degree in a quantitative field (Data Science, Mathematics, Statistics, Economics, CS, etc.)
• 5+ years experience in applied analytics within risk, compliance, fraud, lending, or similar decisioning domains
• Experience designing, implementing, and monitoring high-impact decisioning or policy frameworks
• Strong SQL skills and experience navigating complex data environments, combined with proficiency in Python for data analysis (NumPy, Pandas, Sklearn) and familiarity with statistical modeling, A/B experimentation, and other analytical techniques for driving data-informed decisions.
• Proficiency in defining, implementing, communicating, and monitoring performance metrics with diverse stakeholders including Product, Machine Learning, Operations, Legal, and external partners
• Understanding of regulatory compliance concerns and the ability to design solutions that balance business needs with legal requirements
• Proven track record of tackling ambiguous business challenges with minimal guidance and applying analytical/statistical methods to tackle real-world problems using big data
• Comfort writing and documenting clean, organized, and testable code and contributing to software applications that implement data science and analytical artifacts in pipelines or front-ends.

Nice To Haves

• Experience with financial crimes compliance systems, technologies, and processes.
• CAMS or CFCS certifications

Responsibilities

• Design and implement automation strategies in our in-house rule engines that support regulatory compliance objectives, particularly within transaction monitoring and sanctions domains
• Translate complex regulatory requirements and analytical insights into clear, actionable recommendations for cross-functional stakeholders
• Develop detection policies and decisioning frameworks that are legally defensible and operationally sound
• Proactively identify new opportunities to improve risk automation and compliance outcomes through statistical modeling, experimentation, and data analysis
• Collaborate with Machine Learning teams on model evaluation, governance, and operationalization of model outputs for decision-making
• Ensure high-quality documentation, monitoring, and validation of risk actions that impact customers and operational teams

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level