Job Description
We are seeking a highly analytical and business-savvy Business Analyst to join our Inventory Placement team. In 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.
Basic Qualifications
- 1+ years of data analytics or automation experience
- 1+ years of capacity planning, operations planning, business analysis or similar experience
- Bachelor’s 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
Preferred Qualifications
- Bachelor’s 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)
- Background in supply chain, inventory management, demand forecasting, or fulfillment network analytics
- Strong written communication; comfortable writing 1–2 page narratives backing recommendations with data
