Description:
Deliver rigorous, end-to-end analytics across customer and digital channels to inform strategy and drive measurable business impact. Own the integrity of digital data (e.g., Adobe Analytics), design and evaluate experiments, build customer segmentation/models, and translate findings into clear recommendations for omni-channel retention, reactivation, and acquisition.
The impact you can have
- Serve as the go-to for digital data and metric definitions; govern tracking logic and business rules in Adobe Analytics (error identification, resolution recommendations, testing, and validation).
- Partner with Ecommerce/Marketing/Engineering and vendors to fix/add tracking and manage end-to-end QA across Dev/Test/QA/Prod environments.
- Build and maintain reporting that enables a daily POV on ecommerce performance; optimize report design in in-house tools.
- Develop robust customer segmentation and predictive models (e.g., clustering, regression, decision trees) to optimize target marketing, promotions, and loyalty efforts; implement models into business workflows.
- Tie online behaviors to offline purchases and demographics to deepen customer understanding and drive omni-channel strategies.
- Execute sound test design (A/B, multivariate): sampling, tailored success metrics, and statistical significance (chi-square, t-test, ANOVA, correlation).
- Translate business questions into technical requirements; synthesize findings into actionable recommendations aligned to revenue, margin, and customer KPIs.
- Proactively communicate status, set expectations, and create concise, executive-ready narratives and visuals that guide action.
- Partner across Ecommerce, Email, Online Marketing, Merchandising, Loyalty, Stores, Finance, and Planning to prioritize and deliver impact.
- Leverage modern AI/LLM tools to improve efficiency in code development, documentation, and context capture.
You’ll bring to the role
- Bachelor’s degree in a quantitative field such as applied math, statistics, engineering, economics, computer science (or similar).
- 1-3 years of relevant work experience spanning online and offline data.
- Proficiency in SQL and statistical software such as R, Python, or SAS.
- Experience with Adobe Analytics / Adobe Workspace and advanced Excel (pivot tables, formulas).
- Experience with data wrangling tools and techniques such as joins, filters, imputation, fuzzy matching.
- Experience with statistical significance techniques such as t-test, ANOVA, correlation, or others.
- Experience using statistical techniques such as regression, clustering, survival analysis, decision trees, event-based modeling.
- Strong quantitative, analytical, and problem-solving skills.
- Ability to manage multiple projects and deliver against aggressive deadlines.
- Experience troubleshooting and/or debugging and translating requirements into technical specifications.