Sr Analyst Performance & Insights

Job description

Pyramid Overview Roundel is Target’s retail media network. Roundel designs and delivers impactful marketing for brands and their agencies, resulting in engagement and incremental sales that can be measured online and in-store, all within premium, brand-safe environments. About the Job The Performance & Insights team enables advertisers to measure, understand, and optimize the business impact of their media investments through advanced analytics, measurement strategy, experimentation, visualization, data-driven storytelling, and emerging AI-enabled analytical capabilities. As a Senior Analyst, Performance & Insights, you will lead scaled and custom analytics initiatives that improve advertiser outcomes and advance Roundel's analytical capabilities. You will translate complex business questions into structured analytical approaches, apply advanced statistical and measurement techniques, and develop actionable recommendations that support better media and investment decisions. A key focus of this role will be turning recurring analytical questions into repeatable capabilities through reusable frameworks, automated analyses, dashboards, statistical models, and modular solutions adopted across advertisers, categories, campaigns, and Performance & Insights teams. You will strengthen statistical rigor by applying established statistical tests, experimental designs, regression models, and time-series methods; validating findings; and establishing clear, defensible criteria for interpreting results. Success in this role requires strong analytical judgment, hands-on applied statistical and causal measurement expertise, digital media measurement knowledge, technical proficiency, visualization and storytelling skills, consultative problem-solving, and the ability to work across business, analytics, and technology teams. Key Responsibilities · Measurement strategy & expertise: Translate business questions into practical analytical and measurement approaches, choosing suitable methods and explaining assumptions, bias and limitations. Statistical rigor & evidence validation: Apply statistical tests, confidence intervals, power and sample-size calculations to assess performance differences and determine whether results are meaningful. Develop predictive and diagnostic analytical capabilities: Use regression, time-series and predictive analysis to understand performance drivers, conversion behavior, seasonality and potential growth or investment opportunities Lead and deliver custom analytics projects for the P&I team: Deliver custom analyses of campaign, audience, creative and customer performance, for existing and emerging business questions Productize repeatable analytical work: Convert recurring analyses and business questions into reusable modules, frameworks, datasets, metrics, code packages, dashboards, and self-service products with clear inputs, quality checks, statistical validation and guidance for interpreting results. Analytical storytelling & decision support: Present clear recommendations, work with business, measurement, product and data teams, and help analysts adopt new methods and tools. Partner cross-functionally: Work with Product, Measurement, Data Strategy, GTM, and P&I teams to align analytical capabilities with business needs. Responsible GenAI usage: Explore responsible uses of GenAI to simplify analytical workflows, automate routine work and support insight generation while maintaining appropriate validation and oversight. About you: 5+ years of experience in marketing analytics, retail analytics, measurement, data science, or a related analytical discipline. Master's degree in Statistics or Economics, Data Science, Analytics or a related quantitative field. Strong hands-on knowledge of descriptive statistics; hypothesis testing (t-tests and z-tests); confidence intervals; Pearson and Spearman correlation; proportion and chi-square tests; and the ability to interpret meaningful performance differences and uncertainty. Practical experience with A/B testing and experimental design, including test/control groups, randomization, statistical power, and sample-size calculations. Ability to assess bias, assumptions, and limitations and explain whether results support a business conclusion. Ability to apply linear, multiple linear and logistic regression, time-series analysis, and outlier detection or robust statistics to business problems. Advanced SQL and working proficiency in Python for statistical analysis and reusable workflows; experience with relevant libraries such as pandas, NumPy, SciPy or statsmodels and cloud platforms such as GCP or Azure. Good to have: ANOVA, bootstrap methods, multiple-comparison corrections, matched controls, difference-in-differences, segmentation/clustering, response models or other advanced predictive and causal techniques. Hands-on familiarity with Generative AI and large language model applications in analytical workflows, including areas such as prompt design, code assistance, analytical agents/workflows, governed knowledge retrieval, and automated synthesis. Experience building analytical solutions and communicating findings clearly, with working knowledge of BI tools and practical GenAI applications. Strong problem-solving, collaboration and stakeholder communication skills.