Description
The Performance & Insights team at Roundel, Target's retail media network, enables advertisers to measure, understand, and optimize their media investments through advanced analytics and measurement strategies. 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.
Key responsibilities include:
- Developing measurement strategies and expertise to translate business questions into practical analytical approaches
- Applying statistical tests and validation to assess performance differences and determine meaningful results
- Creating predictive and diagnostic analytical capabilities using regression, time-series analysis, and predictive modelling
- Leading and delivering custom analytics projects for the Performance & Insights team
- Productizing repeatable analytical work into reusable modules, frameworks, and self-service products
- Collaborating cross-functionally with business, analytics, and technology teams
- Exploring responsible uses of Generative AI to simplify analytical workflows and support insight generation
Requirements:
- 5+ years of experience in marketing analytics, retail analytics, measurement, data science, or a related field
- Master's degree in Statistics, Economics, Data Science, Analytics, or a related quantitative field
- Strong knowledge of descriptive statistics, hypothesis testing, and statistical analysis
- Practical experience with A/B testing, experimental design, and statistical power calculations
- Proficiency in SQL, Python, and relevant libraries such as pandas, NumPy, and SciPy
- Familiarity with 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.