Senior Data Analyst

Key Responsibilities:

Data Analysis
Analyze client vs. competitor pricing datasets to identify price gaps, margin exposure, assortment gaps, stock, and MSRP trends.
Surface meaningful trends, patterns, and business insights from large datasets.

Data Quality
Audit Product Matching decisions against client-specific match taxonomies. Human-in-the-Loop Product Matching - Review AI-assisted matches, identify mismatches and edge cases, and provide feedback to improve matching accuracy.
Perform data quality checks e.g. missing fields, duplicates, pricing logic, discounts, case quantity/UOM, URLs, images, brand consistency, and match confidence.
Identify systemic data defects such as source-level errors.
Prepare validated datasets, issue summaries by reason and severity, and clientready reports.
Cross-Functional Collaboration Work with Product, Data, Engineering, and Analytics teams to investigate and resolve data concerns.
Collaborate with senior analysts, product managers, leadership, and clients to improve data quality and analytical processes.
Proactively communicate data-quality issues, risks, dependencies, and blockers.
Identify opportunities for process improvement and better use of data.
Required Skills & Experience:

5–7 years of experience as a Data Analyst
Strong Excel and SQL; Python with pandas for larger datasets