Director, CECL Analytics and Loss Forecasting

• →Lead strategic business initiatives integrating loss forecasting capabilities with business strategy execution, risk appetite development, and regulatory compliance across commercial real estate, commercial & industrial, agriculture, retail consumer, and commercial business lending portfolios.
• →Develop, and maintain appropriate CECL loss forecasting models for commercial portfolios leveraging Moody's dual score matrices and portfolio segmentation approaches that recognize unique characteristics of CRE (property types, geographic concentrations), C&I (industry sectors, cash flow dynamics), agriculture (commodity cycles, seasonal variations), and retail consumer products.
• →Lead continuous enhancement of CECL qualitative assessments and write-ups, ensuring comprehensive explanations of portfolio-specific risk factors, economic adjustments, and management overlays that support quantitative model outputs.
• →Ensure models meet regulatory standards including SR 11-7, while serving as primary liaison with internal and external regulators, auditors, and vendors on ongoing CECL-related matters and examinations.
• →Develop and communicate advanced business intelligence that connects loss forecasting results to management decisions, macroeconomic trends, and organizational objectives across wide business audiences.
• → Independently initiate, conduct and manage complex credit risk projects, including project design, data collection, analysis, summarization, presentation of results and recommendations, and implementation support.
• →Provide strategic guidance and technical mentorship to analysts and business leaders across the organization, building organizational capabilities through expertise sharing, training initiatives, and strategic consultation that enhance enterprise credit risk management.

• Bachelor’s degree in data science, mathematics, statistics, finance, economics, or related field required.

• 8+ years of experience in highly analytical business functions, including at least 5 years in Credit Risk, modeling or related fields.

• 3+ years of experience using Python programming, and SQL with a focus on data analysis, financial modeling, and expert knowledge of Excel. 
• Strong knowledge of working with cloud-based data warehousing solutions (e.g., Snowflake)
• Demonstrated excellent oral and written communication skills.
• Demonstrated ability to handle stress, meet deadlines and work independently.
• Experience in banking or financial services is preferred.

• Deep knowledge of commercial real estate, commercial & industrial, agriculture, retail consumer, and small business lending products and credit risk characteristics.
• Demonstrated leadership abilities with experience managing projects and/or teams in a technical environment.
• Ability to manage multiple complex projects simultaneously while meeting critical deadlines.
• Extensive knowledge of statistical and data science methods applied in the finance industry along with advanced programming skills.
• Ability to work with data to identify complex business trends and propose solutions
• Ability to build consensus and influence the organization in order to achieve business goals.
• Experience with loss forecasting and stress testing at a financial institution, preferably a CCAR institution.

This role may have a specific starting pay within this range.

Final compensation offer to candidate may vary from posted hiring range based upon work experience, education, and/or skill level.

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