This is a remote role that may be hired in CA only. This position provides risk analytics and expert support at the highest level of operational complexity to business units. Creates methods to evaluate potential losses, and develops high-impact solutions to minimize or eliminate risk. Recommends and monitors enhancements to current processes and procedures, performing analysis and reporting in support of strategic objectives. Serves as a resource and may provide a leadership role for the work group through knowledge in the area of specialization.

• Identifying Risk - Leads the design and implementation of process evaluation methods, and the development of expert solutions to address identified risks. Works closely with management to ensure risk strategies are effective and compliant. May involve creation, evaluation, and execution of models or simulation scenarios to test risk conditions.
• Data Analysis - Sources, compiles, and interprets data. Performs complex analysis for risk trends and data discrepancies, and may direct the analytics efforts of the work group.
• Reporting - Produces reports based on data analysis, company trends, and risk factors. Conveys patterns, problems, and areas of improvement. Enables insight into potential losses and mitigation of identified risks through reporting activities.
• Operational Support - Supports business processes through a variety of escalated operational tasks. Develops, implements, and ensures continuous improvement of procedures. Acts as a resource to management and other associates, including production of documentation, presentations, or other materials to educate on risk policies and procedures. Handles complex technical matters and participates in special projects.

Bachelor's Degree and 4 years of experience in Risk management, or financial analysis, or statistical modeling OR High School Diploma or GED and 8 years of experience in Risk management, or financial analysis, or statistical modeling.

Preferred Qualifications:

• Advanced degree (Master's or Ph.D.) in a quantitative field (e.g., Statistics, Data Science, Financial Engineering, Mathematics, Economics, or a related quantitative discipline).
• 5+ years of relevant experience in model development, model validation, or model implementation within the financial industry, is preferred.
• Proficiency in both traditional statistical methods and machine learning techniques; Advanced programming skills (e.g., Python, R, SAS, SQL).
• Strong understanding of regulatory requirements, particularly those related to stress testing and capital planning.
• Excellent problem-solving skills, attention to detail.
• Excellent written and verbal communication skills.
• Experience at a Large Financial Institution (LFI) with knowledge of regulatory guidance and expectations.