AM Digital Marketing

Retail Media Data & Insights Analyst

Role Overview

A Retail Media Data & Insights Analyst who will play a critical role in analyzing performance data from key retail and eCommerce partners — including Amazon, Amazon, Lowe’s, Home Depot, Costco, Criteo and other key retail partners — to uncover actionable insights, trends, and optimization opportunities.

This role is analysis & insight-first, not dashboard-first. You will dig deep into campaign reports, identify performance drivers, and deliver strategic recommendations to business stakeholders.

The ideal candidate has a strong analytical foundation, understands Amazon Retail Media dynamics, and can translate data into clear business stories that drive better decision-making across media investments, product categories, and profitability.

Key Responsibilities

1. Campaign & Performance Analysis

• Analyze campaign data across Amazon Ads, Retail Media+, and Criteo.
• Identify performance trends, category insights, and SKU-level opportunities to optimize ROAS, CTR, CVR, and spend efficiency.
• Conduct deep dives (“double/triple-clicks”) into platform reports to explain what’s happening across retailers.
• Compare performance by platform, campaign type, and category to highlight areas for growth or efficiency.

2. Cross-Retailer Reporting & Consolidation

• Aggregate and normalize performance data from multiple retailer sources into a unified format.
• Track weekly, monthly, and quarterly trends — including sales, traffic, and ad spend across all partners.
• Build and maintain Excel-based performance trackers until automation (Power BI) is implemented.
• Support finance and media teams in validating data accuracy and consistency across reports.

3. Insights Generation & Storytelling

• Develop weekly and monthly insights decks with clear summaries: “What happened, why it happened, and what to do next.”
• Highlight drivers behind spend efficiency, conversion drops, or sales spikes by SKU or retailer.
• Present actionable recommendations to stakeholders (Media, Marketing, Finance).
• Identify halo effects and cross-channel impacts (e.g., Retail Media spend influencing organic sales).

4. Profitability & Incrementality Support

• Support profitability and incrementality modeling by providing clean, validated input data.
• Partner with Finance to ensure SKU-level and category-level financial accuracy.
• Assist in interpreting results from incrementality and profitability tests (Meta, Google, Amazon DSP).

5. Continuous Improvement

• Develop consistent data QA and trend validation processes.
• Collaborate with internal analytics and automation teams to transition manual reports into Power BI dashboards later.
• Maintain clear documentation of all data sources, file structures, and metric definitions.

Required Skills & Experience

Technical Skills

• Advanced Excel (Pivot tables, Power Query, Macros, VLOOKUP/XLOOKUP, data modeling)
• SQL (intermediate) or Python (Pandas, NumPy) – for ad-hoc data manipulation and cleaning
• Experience working with Amazon Ads Console, Amazon Vendor Central, or Amazon Retail Analytics (ARA/NAR)
• Understanding of key retail media metrics — ROAS, CTR, CVR, AOV, DPVR, iROAS, SOV, margin
• Experience consolidating reports across multiple retailers and ad platforms

Analytical & Business Skills

• Proven ability to identify trends, detect anomalies, and explain data stories clearly
• Strong command over profitability, margin, and contribution analysis
• Excellent communication and data storytelling skills — both written and verbal
• Detail-oriented, with a problem-solving mindset and strong data integrity focus

Preferred Skills

• Advanced Excel, VBA Macros, vlookup, pivots,
• Understanding of incrementality testing concepts (A/B, holdout, synthetic control)
• Hands on experience with SQL Intermediate
• Familiarity with profitability modeling and ROI forecasting

Key KPIs / Success Metrics

• Quality and timeliness of weekly/monthly insight reports
• Accuracy and consistency of retailer performance data
• Actionability of insights (alignment with optimization decisions)
• Collaboration effectiveness with Media and Finance teams
• Smooth transition of manual reports into future automated dashboards