Vice President, Data Analytics & Reporting

JOB DUTIES: Vice President, Data Analytics & Reporting with Goldman Sachs Bank USA in New York, New York. Evaluate relevance of new collections initiatives related to assistance programs including making business cases for new strategies and estimating and measuring the potential impact of existing initiatives. Data analysis and presentations related to performance of delinquent card portfolios to senior management distilling key findings into consumable insights and communicating to leadership and internal and external stakeholders. Work with Legal, Compliance, Engineering and Product stakeholders to drive new projects and make enhancement to existing processes. Use advanced data analytics to create risk segmentations based on multivariate analysis that are used to build new strategies. Keep up to date with applicable regulations and compliance requirements for possible interactions with internal and external regulators. Build and monitor an exhaustive set of detective controls and own remediations for control breaches while working with stakeholders for fixes on credit card collections products. Statistical analysis for determining test volumes, measuring significance of results using t-tests, and determining optimal strategy for the business. JOB REQUIREMENTS: Bachelors degree (U.S. or foreign equivalent) in Financial Engineering, Data Analytics, Business Administration or Business Analytics, Statistics, Operations Research, or relevant field such as Mining Engineering and five (5) years of experience in the job offered or in a related role. Prior work experience must include five (5) years with the following: flagging and monitoring causal effects and trends in consumer finance and evaluating associated risk-splitters; stakeholder management in the retail banking industry including working with Legal, Compliance, Product, Engineering and Operations; collections related regulations and compliance requirements including FDCPA, UDAAP, TILA (Reg Z) and ECOA (Reg B); experience with credit risk management or collections risk management; SQL and data manipulation through Python and PySpark; performing statistically driven data analyses using a variety of analytical techniques and data sources including Databricks, Snowflake, Tableau, and Excel; and developing analytical reports and presentations for senior management, executive committees, and regulatory exams.