**Performance Marketing Analytics - Senior Associate**: As a Senior-level specialist at JPMorgan Chase, you will transform complex data into actionable insights, driving customer acquisition and Owned Media strategy. Key responsibilities include designing experiments, diagnosing performance drivers, and developing scalable data pipelines. Required skills feature advanced SQL, Python or R proficiency, and 2+ years of relevant analytics experience. Collaborate with stakeholders, communicate complex findings, and influence roadmaps across teams. Preferred qualifications include a Master's degree in a related technical field and experience with data visualization tools like Tableau or Alteryx.
Full Job Description
Location: Columbus, OH, United States
Join a team that helps shape how millions of customers discover and choose Chase digital experiences. You will work at the intersection of analytics, data science, and data engineering to turn complex data into clear decisions and scalable solutions.
As a Quantitative Analytics Senior Associate at JPMorganChase within Performance Marketing Analytics, you will own the lifecycle from raw data to executive-ready insight. You will design and interpret experiments, develop analytical frameworks, and build reliable pipelines that help teams move faster with confidence. You will partner with marketing, product, and technology stakeholders to measure performance, optimize customer acquisition, and strengthen Owned Media strategy through data.
Job responsibilities
Identify, integrate, and analyze large, complex datasets from multiple sources to generate actionable insights and recommendationsDesign measurement approaches and experiments (including A/B, multivariate, and holdout designs) to quantify impact and inform decisionsInterpret experimental results using primary and guardrail metrics, statistical significance, and practical business impactDiagnose performance drivers through segmentation, funnel analysis, and anomaly detection (for example: device, customer type, drop-off points, traffic allocation, and logging gaps)Build and maintain scalable, production-ready data pipelines and analytical frameworks that enable repeatable reporting and insightsWrite secure, stable, testable, and maintainable code using SQL and Python or R, with strong attention to quality and controlsCommunicate complex findings through clear narratives and visualizations; present to senior stakeholders and influence roadmaps and prioritiesStay current on innovations in analytics and responsibly use approved AI-assisted analytics tools to accelerate development, documentation, and issue triageRequired qualifications, capabilities and skills
Bachelors degree in Data Science, Computer Science, or a related technical field2+ years of applied experience in analytics, software engineering, or a related fieldHands-on experience with system design, application development, testing, and operational stabilityStrong SQL skills and experience working with relational databases to extract, manipulate, and analyze dataExperience building analytical solutions across multiple data sources, with attention to data quality and reproducibilityAbility to manage multiple priorities independently with strong organization and attention to detailStrong written and verbal communication skills, with the ability to distill complex findings into clear, concise insights for varied audiencesExperience translating analytical outcomes into business actions in partnership with cross-functional stakeholdersPreferred qualifications, capabilities and skills
Masters degree in Data Science, Computer Science, or a related technical fieldExperience with data visualization or workflow tools (for example: Tableau or Alteryx)Proficiency in Python or R for analysis and automationExperience applying machine learning and generative AI tools to automate workflows and deliver insights, with a responsible and compliant approachUnderstanding of responsible AI practices, including data sensitivity considerations and secure handling of inputs and outputs Turn marketing and product data into experiments, insights, and data products that improve digital customer acquisition. 
