Decision Scientist

Decision Scientist - Financial Crime Risk & Transaction Monitoring We are seeking a Decision Scientist to design, develop, and implement automated risk decisioning frameworks that support regulatory compliance and mitigate financial crime risk. This role will focus on developing data-driven risk policies and decisioning strategies within Transaction Monitoring, Sanctions, and Disputes operations. The role involves applying advanced analytics, statistical techniques, and risk policy design to identify emerging risks, improve automation, and strengthen regulatory compliance. The Decision Scientist will build analytical frameworks, evaluate heuristic and machine learning-driven decisions, and develop scalable and defensible risk policies that support operational teams responsible for financial crime investigations. This position requires close collaboration with Compliance, Risk, Machine Learning, Operations, Engineering, Legal, and Product teams to ensure risk mitigation strategies effectively balance regulatory requirements, loss prevention, and customer experience.Key Responsibilities Risk Decisioning & Policy Development • Design and implement automated decisioning strategies within internal rule engines to support regulatory compliance objectives across transaction monitoring and sanctions screening programs. • Develop risk detection policies and decisioning frameworks that are operationally scalable and legally defensible. • Translate regulatory requirements and analytical insights into clear risk policies and automated controls. Risk Analytics & Automation • Apply data analysis, statistical modeling, and experimentation to identify opportunities to improve risk detection and automation. • Develop analytical frameworks to evaluate heuristic rules, automated decisions, and machine learning outputs used in risk management processes. • Identify opportunities to improve operational efficiency and regulatory compliance through data-driven decisioning strategies. Machine Learning Collaboration • Partner with Machine Learning and Data Science teams to evaluate model performance and ensure model outputs can be effectively operationalized for decision-making. • Support model governance, validation readiness, and monitoring frameworks for risk-related ML models. Governance, Monitoring & Documentation • Ensure strong documentation, monitoring, and governance of automated risk decisions impacting customers and operations teams. • Define and monitor performance metrics, detection effectiveness, and operational impact of risk policies and decision frameworks. • Maintain audit-ready documentation aligned with regulatory expectations and internal compliance standards. Cross-Functional Collaboration • Work closely with Compliance, Risk, Operations, Engineering, Legal, and Product stakeholders to ensure risk strategies are operationally feasible and regulatory compliant. • Communicate analytical insights and policy recommendations to technical and non-technical stakeholders. Required Qualifications Education • Advanced degree in quantitative fields such as Data Science, Statistics, Mathematics, Economics, Computer Science, or related discipline. Experience • 5+ years of experience in applied analytics within risk, financial crime compliance, fraud, lending, or decisioning environments. • Experience designing and implementing risk decisioning frameworks, detection policies, or automated risk controls. Technical Skills • Strong SQL skills and experience working with complex data environments. • Proficiency in Python for data analysis (NumPy, Pandas, Scikit-learn). • Experience with statistical modeling, A/B testing, and data-driven experimentation. • Familiarity with building analytical artifacts that support automated decision pipelines or operational systems. Analytical & Business Skills • Ability to define and monitor risk performance metrics and operational KPIs. • Strong ability to translate complex analytical findings into actionable business recommendations. • Experience solving ambiguous business problems using data and analytical techniques. Governance & Compliance Awareness • Understanding of regulatory compliance considerations in risk and financial crime environments. • Ability to design solutions that balance regulatory expectations, operational feasibility, and customer experience. Preferred Qualifications • Experience working with financial crime compliance systems or transaction monitoring platforms. • Familiarity with AML, sanctions screening, and financial crime regulatory requirements. • Professional certifications such as CAMS or CFCS.