In Goldman Sachs Bank USA, we offer a wide range of solutions to help our customers meet their financial goals. Our teams seek to provide the highest level of customer service and support in everything we do. The Bank offers high yield savings accounts and a variety of loan products to individuals and private bank, corporate and community clients. Our savings products include an online savings account and certificates of deposit in a variety of terms.

Asset & Wealth Management

The Asset & Wealth Management Division include Goldman Sachs Asset Management (GSAM), Private Wealth Management (PWM) and Marcus Savings. We provide asset management, wealth management and banking expertise to consumers and institutions around the world. AWM partners with various teams across the firm to help individuals and institutions navigate changing markets and take control of their financial lives.

Marcus Savings

Marcus Savings business is comprised of the firms digitally led consumer business, combining the strength and heritage of a 150-year-old financial institution with the agility and entrepreneurial spirit of a tech start-up. Through the use of machine learning and intuitive design, we provide customers with powerful tools that are grounded in value, transparency and simplicity to help them make smarter decisions about their money.

Summary: 
The Marcus Savings team is seeking a consumer-centric, analytically minded, creative, and energetic Associate to join the US Commercial Strategy team. In this role youll apply your consumer financial services industry experience and analytical skill sets to drive the analytics strategy, data infrastructure, and model development to drive growth and engagement of our Savings and CD products.

In your role: 

• Analyze customer profiles, preferences, behaviors, and market activity to inform target segments, product development, and go-to-market strategy.
• Apply cohort, time-series, and causal inference methods to identify trends, isolate drivers, and measure incremental impact across marketing, product, pricing, and customer experience.
• Build segmentation, lifecycle, and customer lifetime value frameworks for Savings and CD products to improve acquisition quality, engagement and retention.
• Shape go-to-market strategies through opportunity sizing, audience targeting, value propositions, channel strategy, and launch measurement.
• Develop dashboards and measurement frameworks to track product and marketing KPIs, operational performance, customer outcomes, and benchmarks.
• Analyze digital journeys and conversion funnels to identify friction and recommend customer experience improvements.
• Design and evaluate A/B tests, multivariate tests, and quasi-experimental analyses to measure statistical significance, incrementality, and acquisition and retention impact.
• Build and automate reporting, analytical tools, and ML models for churn, lifetime value, segmentation, and price sensitivity owning design through deployment and monitoring and measure success on both model accuracy and business impact (retention, margin, ROI)

Qualifications:

• 3-5+ years of experience with analytics, metrics, modeling, and reporting in the financial services industry; consumer banking preferred
• Bachelor or Advance degree in quantitative areas like Applied Math, Statistics, Engineering, Computer Science or related disciplines
• Prior experience developing data driven strategies in a deposits business or with B2C marketing analytics is preferred
• Experience in customer analytics, including customer profiling, segmentation, and lifecycle analysis, and applying causal inference methods to measure incremental business impact.
• Strong quantitative and analytical skills and experience in working with large data sets and Big Data tools and stack (e.g., SQL, Hadoop, etc.).
• Experience with Tableau, Power BI or similar data visualization tools
• Experience with programming languages such as Python is preferred.
• Understand and make recommendations to enhance data processes within one or more databases (Oracle, Sybase, Snowflake, etc.) to improve application of data in making business decisions.
• Experience with customer segmentation and applying appropriate machine learning techniques (regression, classification, clustering, NLP, etc.).
• Strong project management skills; self-driven; ability to work independently and cross-functionally
• Demonstrate an ability to effectively communicate and present results highlighting the broader commercial and strategic impact