AWM-Marcus by Goldman Sachs, Marketing Analytics, Associate/Analyst Richardson, TX,

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. 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, modeling, engineering, and product 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. 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. 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. Technical Competency Requirements Identity & Privacy: LiveRamp, Snowflake Data Clean Rooms, InfoSum Measurement Platforms: Google Ads Data Hub (ADH), Amazon Marketing Cloud (AMC) Advanced Analytics: Meta Robyn (MMM), GeoLift Causal Inference: Microsoft EconML, CausalML, Propensity Score Matching Data Stack: SQL, Python, Snowflake, Alteryx, BigQuery, Tableau / PowerBI Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran's status, disability, or any other characteristic protected by applicable law. #J-18808-Ljbffr Goldman Sachs