Job Description

Overview

Vice President, Data Analytics with Goldman Sachs Bank USA in Wilmington, Delaware. Remote work permitted 2 days per week within commuting distance of Wilmington, DE.

Responsibilities

• Perform and oversee advanced data analytics (e.g., machine learning) activities while monitoring portfolio health and identifying opportunities to drive industry-leading fraud prevention and exceptional customer experience.
• Leverage advanced modeling techniques to build forecasting models and machine learning techniques to understand the drivers of portfolio performance trends and identify solutions for improvements.
• Work closely with Business, Product, Technology, Operations, and Compliance teams to implement solutions and improve the performance of the portfolios.
• Identify, document, and improve existing processes to maximize efficiency in constantly evolving environments.
• Provide analysis, design strategies for strategic projects and drive end-to-end project delivery.
• Prepare executive presentations, lead strategy and capability planning, and organize team meetings and activities.
• Research and remain current on the latest industry trends. Introduce new data analysis methodologies.

Qualifications

• Master's degree (U.S. or foreign equivalent) in Computer Science, Software or Computer Engineering, Information Technology, or a relevant quantitative field such as Chemical Engineering, and two (2) years of experience in the job offered or a related role, or
• Bachelor's degree (U.S. or foreign equivalent) in Computer Science, Software or Computer Engineering, Information Technology, or a relevant quantitative field such as Chemical Engineering, and five (5) years of experience in the job offered or a related role.
• Prior experience must include two (2) years with a Master's or five (5) years with a Bachelor's with the following:
• performing and overseeing advanced data analytics (including machine learning) activities while monitoring portfolio health and identifying opportunities to drive fraud prevention;
• data mining using Python and creating tables to monitor incoming disputes and using CHAID analysis to target incoming fraud for rule development identifying high risk transactions at low false-positive rates;
• leveraging advanced modeling techniques to build forecasting models and machine learning techniques to understand drivers of portfolio performance trends and identify solutions for improvements;
• experience with changes to recovery rates of card-not-present transactions based on 3D Secured Merchants and Point-of-Sale entry mode for each transaction;
• working closely with Business, Product, Technology, Operations, and Compliance teams to implement solutions and improve the performance of the portfolios including developing new flags and queuing for high-risk account reviews and fraud servicing;
• identifying, documenting, and improving existing processes to maximize efficiency including experience with customer contact strategies and use of wallet notifications, and one time pass codes to detect and resolve fraud disputes;
• providing analysis and designing strategies for strategic projects and drive end-to-end project delivery including experience with lost interchange revenue, customer attrition, operational costs, and fraud avoidance.

Equal Opportunity

The Goldman Sachs Group, Inc., 2025. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability, or any other characteristic protected by applicable law.

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