Individual contributor role leading strategic business initiatives integrating loss forecasting capabilities with business strategy execution, risk appetite development, and regulatory compliance across consumer and commercial lending portfolios.
Serve as trusted advisor to executive leadership, providing strategic insights that connect loss forecasting results to business performance, market opportunities, and strategic decision-making.
Utilize advanced statistical and programming skills to develop sophisticated loss forecasting models for FNBO's consumer installment loans and card portfolios across both consumer and commercial segments.
Apply sophisticated econometric techniques including regression analysis, time series modeling, survival analysis, and portfolio segmentation approaches consistent with industry best practices and regulatory guidance.
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.
Develop and communicate advanced business intelligence that connects loss forecasting results to management decisions, macroeconomic trends, and organizational objectives across wide business audiences.
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.
Drive ongoing improvement of qualitative methodologies, model validation processes, and documentation standards while ensuring regulatory compliance.
Drive business innovation through enhanced loss forecasting methodologies and process automation that support business growth and operational efficiency.
Provide strategic guidance and technical mentorship to analysts and business leaders across the organization on complex analytical projects, modeling techniques, and qualitative assessment methods.
Build organizational capabilities through expertise sharing, training initiatives, and strategic consultation that enhance enterprise credit risk management including both quantitative and qualitative analysis expertise.

Requirements

Master's degree or PhD in data science, mathematics, statistics, finance, economics, or related field required.
8+ years of experience in highly analytical business functions, including at least 4 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) and version control systems (e.g. Git).
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.
Candidates must possess unrestricted work authorization and not require future sponsorship.

Benefits

Medical, Dental, Vision Insurance
401k, With Matching Contributions
Time Off Programs
Health Savings Account (HSA)/Dependent Care
Employee Banking
Growth Opportunities
Tuition Assistance
Short-Term/Long-Term Disability Insurance

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

loss forecastingregression analysistime series modelingsurvival analysisportfolio segmentationdata analysisfinancial modelingPythonSQLExcel

Soft Skills

strategic insightscommunication skillsstress managementdeadline managementindependencementorshiporganizational capabilitiesexpertise sharingconsultationanalytical project guidance

Certifications

Master's degreePhD