Title: Finance Transformation – Statistical Modeling Manager Location: remote US, EST or CST working schedule Duration: 6 months, with possible extensions. Pay Rate: $77/hr. - $94/hr. Must have skills: Statistical modeling and forecasting experience. Python (must have) or R (highly desired) programming skills. About the Role: We are seeking a dynamic and visionary Finance Transformation – Statistical Modeling Manager to spearhead the development and application of advanced statistical forecasting models in support of our finance transformation journey. This leader will leverage tools such as Python and R to design, implement, and maintain innovative portfolio- and enterprise-level vintage forecasting models. These models will generate actionable insights, enhance decision-making, and drive strategic value for the business. Key Responsibilities: Lead the end-to-end development, validation, and deployment of statistical and machine learning models for portfolio and enterprise-level vintage forecasts. Partner closely with finance, risk, growth, strategy, and technology stakeholders to gather requirements and translate business needs into robust modeling solutions. Drive the exploration and adoption of emerging modeling techniques and technologies to ensure best-in-class forecasting capabilities. Communicate complex modeling concepts, results, and implications to senior leadership and non-technical partners in a clear and compelling manner. Ensure rigorous model governance, documentation, and compliance with regulatory standards and internal controls. Oversee the integration of models into business processes and analytical platforms; monitor ongoing model performance and recalibrate as needed. Identify opportunities to automate and streamline analytics and forecasting across the finance organization. Required Qualifications: Bachelor’s Degree in Statistics, Mathematics, Quantitative Finance, Computer Science, Engineering, or a related quantitative field and 8+ years of experience in statistical modeling and forecasting, preferably within financial services, consumer lending, or a highly regulated environment or; Masters’s Degree in Statistics, Mathematics, Quantitative Finance, Computer Science, Engineering, or a related quantitative field and 5+ years of experience in statistical modeling and forecasting, preferably within financial services, consumer lending, or a highly regulated environment. 5+ years of hands-on proficiency with programming languages such as Python, R, or equivalent tools; experience building production-grade statistical and/or machine learning models. 3+ years of demonstrated leadership experience managing and developing high-performing teams. 3+ years of proven track record in designing and implementing vintage forecasts or similar predictive models for portfolios or enterprises. Exceptional communication and stakeholder management skills with ability to convey complex concepts to diverse audiences. 3+ years of experience with model risk management practices, controls, and regulatory expectations. Preferred Qualifications: Masters or PhD in Statistics, Mathematics, Quantitative Finance, Computer Science, Engineering, or a related quantitative field. Experience integrating modeling solutions with enterprise finance and data platforms. Prior experience with cloud-based modeling environments (AWS, Azure, GCP). Familiarity with modern front-end data visualization tools (Tableau, Power BI, SAS Viya, etc.). Knowledge of accounting principles, credit risk, and portfolio analytics.