Business Analyst, Inventory Placement

We are seeking a highly analytical and business-savvy Business Analyst to join our Inventory Placement this role you will be the analytical engine behind decisions that determine where inventory sits across our fulfillment network directly impacting customer delivery speed shipping costs and inventory health at scale.
You will partner closely with Program Managers Operations Supply Chain and Tech teams to identify inefficiencies surface insights from large and complex datasets and translate them into actionable recommendations. The ideal candidate is someone who lives and breathes data has strong SQL chops can build dashboards that tell a story and brings sharp business acumen to identify and solve hard ambiguous problems. We are looking for a hands-on operator someone who does not wait for clean data or perfect requirements but rolls up their sleeves digs into the problem and drives it to closure.

Key job responsibilities
Deep-dive analytics: Independently scope design and execute complex analyses on inventory placement network flow regional demand patterns fill rates and outbound shipping cost drivers. Translate raw data into clear actionable business insights.
Dashboard and reporting ownership: Build automate and maintain self-serve dashboards (QuickSight Tableau or similar) that give stakeholders real-time visibility into key placement inventory health and network performance metrics.
SQL and data engineering: Write efficient production-grade SQL on large datasets (Redshift Hive Athena). Build and maintain ETL pipelines data marts and reusable datasets that scale across the team.
Problem identification: Proactively find gaps anomalies and improvement opportunities in placement logic replenishment patterns and inventory positioning often before stakeholders ask. Frame these as business problems with quantified impact.
Drive business decisions: Partner with Program Managers and Category teams to size opportunities run A/B tests or controlled experiments and recommend changes to placement strategy sourcing policies or network design.
Goal and metric ownership: Own the definition tracking and reporting of team-level metrics and weekly/monthly business reviews (WBR/MBR). Investigate variances and root-cause performance misses.
Stakeholder communication: Present findings to senior leadership in crisp data-backed narratives both written documents and verbal reviews. Influence decisions without authority.
Tooling and automation: Identify manual repetitive workflows and automate them using SQL Python or scripting. Continuously raise the bar on team productivity.

- 1 years of data analytics or automation experience
- 1 years of capacity planning operations planning business analysis or similar experience
- Bachelors degree
- Knowledge of data pipelining and extraction using SQL
- Knowledge of SQL and Excel at a moderate or advanced level
- Experience with data mining tools like SQL SAS SPSS or similar

- Bachelors degree in engineering statistics computer science mathematics or a related quantitative field
- 1 years of business analyst data analyst or similar role experience
- Knowledge of writing and optimizing SQL queries in a business environment with large-scale complex datasets
- Experience with reporting and Data Visualization tools such as Quick Sight / Tableau / Power BI or other BI packages
- Knowledge of Microsoft Excel at an advanced level including: pivot tables macros index/match vlookup VBA data links etc.
- Experience in developing and executing an analytic vision to solve business-relevant problems
- Experience using Python or R for data analysis or statistical tools such as SAS
- Knowledge of AWS tech stack (e.g. AWS Redshift S3 EC2 Glue)
- Experience with ETL
- Experience in A/B testing
- Knowledge of methods for statistical inference (e.g. regression experimental design significance testing)
- Preferred Qualifications
- Background in supply chain inventory management demand forecasting or fulfillment network analytics
- Strong written communication; comfortable writing 12 page narratives backing recommendations with data

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