Modeling Analytics [Multiple Positions Available]

DESCRIPTION:

Duties: Deliver analytical results for the consumer lending portfolio to support loss forecasting exercise including Allowances for Loan and Lease Losses (ALLL), budget, Risk Appetite and regulatory stress testing (CCAR and ICAAP) processes. Collaborate with model development, technology, finance, model execution and strategy teams to develop, support and maintain an analytical model, including data analysis, performance monitoring, effective challenge of models results and issue resolution via overlay. Improve the analytical process to enhance efficiency, accuracy of results, and quality of insights. Support consumer lending by driving risk-related strategies. Identify risk drivers to drive, support, and explain key credit decisions to C-level executives and regulators. Provide thought leadership for complex problems to drive results. Document regulatory memos, reports, and other documentation explaining findings and recommendations. Perform design, implementation, measurement and peer review in the credit card industry forecasting trends from the model and translating quantitative information into actionable insights that can be leveraged by both analytic and non-analytic staff. Adopt and implement best practices and standards using Big-data technologies (Spark) to ensure all production processes including business requirements, model execution, model back-testing and validation. Refine the analytical process and ensure precise results, while elevating the quality of insights.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Business Analytics, Finance, Mathematics, or related field of study plus 2 years of experience in the job offered or as Modeling Analytics, Operations Analyst, Business Intelligence Analyst, Data Analyst, or related occupation.

Skills Required: This position requires two (2) years of experience with the following: Developing and automating financial performance reports in Excel VBA, and integrating multi-source data to generate insights on customer behavior and performance trends; Designing and developing large-scale SQL scripts in Teradata and Oracle, integrating complex, structured datasets from multiple sources to enhance data consistency, and analytical reporting for cross-functional teams; Developing automated ETL pipelines for large-scale data ingestion and transformation using Python and SQL; Improving processing efficiency and data accessibility by leading the migration of dashboards from Tableau to Power BI; Consolidating financial performance and risk analytics for senior management review; Providing leadership for junior associates focusing on criticality of financial data and technical aspects of end-to-end process of data extraction, transformation and reporting, resulting in team productivity; Optimizing SQL queries by leveraging advanced techniques including sub-queries, views, Common Table Expressions (CTEs), and window functions; Using QUALIFY statements and EXISTS clauses to streamline data retrieval; Presentations and demos for senior leadership and business users in explaining key risk business indicators; Leading multiple POC (Proof of Concept) report developments and optimized Power BI and Tableau dashboards by gathering requirements, creating and testing reports, and refining calculations to ensure fast loading, dynamic functionality, smooth interaction, and continuous improvement; and Implementing advanced predictive models for data analysis by performing EDA, leveraging statistical techniques and machine learning algorithms such as Linear Regression, Logistic Regression and XGBoost to drive insights and decision-making. This position requires one (1) year of experience with the following: Migrating large-scale data from legacy systems such as MySQL Server, and Teradata to cloud storage solutions including AWS, and S3 using AWS services, ETL processes and automation tools.