Data Insight Analyst

Job Summary:

This role focuses on mid-level analytical and statistical work to support eCommerce growth, marketing efficiency, loyalty activation, and omnichannel performance. You will design analytical solutions, conduct deeper statistical modeling, and support experimentation frameworks that help optimize customer journeys and personalization.

Role and Responsibilities:

Analytical Product Ownership:

• Own mid-sized analytical workstreams such as customer segmentation, eCommerce funnel diagnostics, offer performance analytics, and multi-touch engagement tracking.
• Build robust dashboards incorporating drill-downs, dynamic filtering, and automated data refreshes.

Statistical & Predictive Modeling:

• Apply intermediate modeling techniques including:
• Linear and logistic regression for KPI driver analysis
• Time series (ARIMA, ETS) for forecasting demand or traffic
• Clustering (k-means, hierarchical) for behavior-based segmentation
• Support predictive models such as churn propensity, category affinity, and next-purchase prediction.

Experimentation & Causal Analysis:

• Lead A/B test analysis and compute lift, confidence intervals, and basic CUPED variance adjustments.
• Provide insights on campaign performance, personalization tests, and onsite feature rollouts.

Marketing & Loyalty Insights:

• Conduct analysis of promotion elasticity, offer redemption behavior, campaign ROI, and loyalty engagement (tier migration, reward redemption patterns).
• Build datasets to support marketing automation and customer targeting.

Cross-Functional Collaboration:

• Partner with data engineering teams to shape datasets, ensure pipeline reliability, and validate model performance.
• Present analytical insights to marketing, merchandising, and product teams, shaping tactical decisions.

Required Experience:

• Bachelors or Masters degree in Analytics, Data Science, Statistics, Engineering, or related fields.
• 24 years of experience in analytics with exposure to statistical modeling (retail/eCommerce preferred).
• Strong SQL skills and experience working within cloud platforms (Snowflake, Databricks).
• Hands-on experience with Power BI or Tableau and experience designing analytic-ready data models.
• Working knowledge of predictive analytics and methods such as regression modeling, clustering, uplift modeling, and time-series forecasting.
• Experience using Python for data wrangling, modeling, or statistical analysis is preferred.
• Ability to independently structure analytical problems, validate assumptions, and communicate insights clearly.