Opportunity Overview

As a Marketing Analytics, Associate/Analyst within the Commercial Strategy team, you will sit at the intersection of data science and business growth. You will be responsible for deciphering complex consumer behaviors to optimize marketing spend, improve customer acquisition, and drive the long-term profitability of our digital banking products. This role requires a deep understanding of modern, privacy-centric measurement frameworks and the ability to translate technical findings into commercial strategies.

Asset & Wealth Management

The Asset & Wealth Management Division include Goldman Sachs Asset Management (GSAM), Private Wealth Management (PWM) and Marcus Savings business (MS). 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 by Goldman Sachs

As the online consumer banking business of Goldman Sachs, Marcus operates as a digital bank, providing high-yield savings accounts and Certificates of Deposit (CDs) directly to individual consumers. Marcus combines Goldman Sachs' 150+ years of expertise with intuitive digital experiences, focusing on value, transparency, and simplicity for its millions of customers, and is recognized as the largest pure online bank, delivering a fully digital experience without physical branches.

Responsibilities:

• Advanced Marketing Measurement & Attribution: Develop and maintain measurement frameworks to evaluate the effectiveness of multi-channel marketing campaigns (Search, Social, Display, Email, CTV, Audio/Radio). Join first-party customer data with event-level ad data for deep-dive attribution and audience analysis.

• Privacy-First Identity Resolution: Utilize data clean rooms (e.g. Liveramp, Snowflake, InfoSum) to perform privacy-safe data collaboration and identity stitching across fragmented touchpoints.

• Incrementality & Causal Analysis: Design and execute randomized controlled tests (RCTs) and geo-testing using frameworks like GeoLift to measure the true incremental impact of marketing investments.

• Marketing Mix Modeling (MMM): Conduct Marketing Mix Modeling (MMM) using open-source libraries (e.g., Meta’s Robyn or Google’s LightweightMMM) to estimate marketing contribution and inform marketing budget planning and optimization.

• Causal Inference: Apply advanced statistical techniques and Python libraries (e.g., EconML, CausalML) to move beyond correlation and understand the drivers of customer behavior.

• Automated Reporting: Build and automate high-impact dashboards (e.g. Tableau, PowerBI) to provide real-time insights into marketing ROI, channel performance, campaign double-clicks/deep-dives, promotion effectiveness , and prospect/customer cohort analysis.

• Cross-Functional Collaboration: Work closely with technology and modeling teams to evaluate new data sources and analytical tools, ensuring the marketing stack remains cutting-edge.

• Growth Strategy & Optimization: Use data and statistical testing to identify opportunities for improving conversion rates across the customer acquisition funnel and optimizing Customer Acquisition Cost (CAC).

• A/B Testing & Experimentation: Design, execute, and monitor "test and learn" strategies for marketing creative, landing pages, and promotional offers, ensuring results meet statistical significance.

• Automated Dashboards: Build and automate high-impact visualizations in Tableau to provide real-time insights into marketing ROI and channel performance for senior leadership.

• Cross-Functional Collaboration: Partner with the Modeling, Engineering, and Product teams to integrate new data sources and refine the marketing tech stack.

Qualifications:

• Education: Advanced degree (Master's preferred) in a quantitative field such as Statistics, Applied Mathematics, Engineering, Computer Science, Finance or Economics.

• Experience: 1–2 years of experience in marketing analytics, data science, or commercial strategy, preferably within consumer banking, financial services or a high-growth consumer tech environment.

• Technical Skills:

• Programming: Expert-level SQL and Python (specifically for data science and statistics).

• Marketing Tech: Hands-on experience with LiveRamp, Google Ads Data Hub, and/or Data Clean Rooms.

• Measurement Methodologies: Proven track record in conducting MMM, Geo-testing, and Causal Inference.

• Visualization: Proficiency in Tableau and Advanced Excel.

• Analytical Rigor: Strong understanding of statistical concepts (e.g., regression, hypothesis testing, significance levels).

• Communication: Demonstrated ability to present complex analytical results to non-technical stakeholders, highlighting commercial and strategic impacts.

• Project Management: Self-driven with the ability to manage multiple workstreams independently in a fast-paced environment.