Job Summary
The Decision Science Analyst will analyze business problems and translate business needs into structured analytical requirements, data-driven recommendations, and measurable business outcomes, with a focus on Fraud and Anti-Money Laundering (AML) analytics. The role involves advanced SQL-based analysis, business intelligence, reporting, data transformation, financial impact assessment, and ROI modeling. The analyst will collaborate with business stakeholders, data engineering, and technology teams to develop scalable analytics solutions, improve processes, ensure data quality, and support responsible adoption of Generative AI and Large Language Models (LLMs).
Key Responsibilities
• Analyze business problems and translate business needs into analytical requirements.
• Identify process improvement opportunities and document current-state and future-state processes.
• Develop frameworks to assess the financial impact and return on investment (ROI) of proposed solutions.
• Evaluate alternative approaches and provide data-driven recommendations.
• Gather and document complex business requirements in collaboration with stakeholders.
• Translate ambiguous business questions into structured analytical frameworks.
• Develop and implement business intelligence, reporting, and analytics solutions.
• Support data visualization, data transformation, and data collection processes.
• Contribute to analytical infrastructure, data engineering solutions, and scalable data pipelines.
• Partner with data engineering and technology teams to ensure reliable, high-quality data.
• Apply quantitative and analytical techniques to solve business problems and influence decision-making.
• Create dashboards, reports, and visualizations in accordance with enterprise standards and best practices.
• Leverage Generative AI and Large Language Models (LLMs), where appropriate, to enhance analytics solutions.
• Participate in data governance, performance monitoring, continuous improvement, and responsible AI initiatives.
• Influence data, information, and application architecture decisions through a systems-thinking approach.
Required Qualifications
• 8+ years of experience with advanced SQL.
• Experience with SAS.
• Strong data analysis and analytical problem-solving skills.
• Experience with business intelligence, reporting, and data visualization.
• Experience gathering, documenting, and translating business requirements into analytical solutions.
• Knowledge of data transformation and data engineering concepts.
• Experience with financial analysis and ROI modeling.
• Strong stakeholder management and collaboration skills.
• Excellent written and verbal communication skills.
Preferred Qualifications
• Banking industry experience.
• Experience with credit risk or consumer credit.
• Experience working in large banks or FinTech organizations.
• Exposure to Generative AI and Large Language Models (LLMs).
• Dashboard development experience using Tableau, Power BI, or similar tools.
• Knowledge of data governance practices.
• Experience developing analytics infrastructure.
