Identify patterns, inefficiencies, and improvement opportunities in sourcing and placement decisions.
Surface insights that inform strategic and operational changes.
Analyze drivers by segment, technology, partner profile, activity level, and process step.
Propose meaningful segmentations (e.g. order value buckets, technology subcategories, complexity tiers, partner activity levels).
Build flexible calculation frameworks to estimate the impact of changes such as removing blockers, adjusting lead times, or updating margin or pricing guardrails.
Conduct statistical analyses to evaluate the effectiveness of new features, policies, or process changes.
Work closely with Partner Management, Product, and Operations.

3+ years of hands-on experience in Data Analytics, Operations Analytics, or Business Analytics (preferably in operations, marketplaces, supply chain, sourcing, procurement, or similar domains)
Strong SQL skills and confidence working with multiple datasets and complex joins
Proficiency in Python, with experience using at least one core data library (e.g. pandas, SciPy, scikit-learn)
Solid understanding of statistics and driver/factor analysis
Good understanding of relational database principles
Proven ability to turn analysis into clear, actionable recommendations.

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Data Analyst

Key skills