ASSPL

Business Intelligence, Planning/Development, Logistics

BusinessAnalyst,InventoryPlacement

₹7–10L ~AI est. Bengaluru, Karnataka, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Business Analyst, Inventory Placement at ASSPL. Skills: Inventory Placement, Data Analytics, SQL, Business Acumen. Scope complex analyses. Design complex analyses”

Industry & Context.

Business Intelligence, Planning/Development, Logistics
Problems you'll solve

Analytical; Identify inefficiencies; Surface insights; Actionable recommendations; Solve hard problems; Solve ambiguous problems; Root-cause analysis

What They're Looking For.

Must Have

1+ years data analytics experience, 1+ years automation experience, 1+ years capacity planning experience, 1+ years operations planning experience, 1+ years business analysis experience, Bachelor's degree, Knowledge of data pipelining, Knowledge of data extraction using SQL, Knowledge of SQL, Knowledge of Excel

Nice to Have

Bachelor's degree in quantitative field, 1+ years business analyst role experience, 1+ years data analyst role experience, Writing and optimizing SQL queries, Experience with reporting tools, Experience with Data Visualization tools, Advanced Microsoft Excel knowledge, Experience developing analytic vision, Experience using Python for data analysis, Experience using R for data analysis, Experience with SAS, Knowledge of AWS tech stack, Experience with ETL, Experience in A testing, Knowledge of statistical inference methods, Background in supply chain, Background in inventory management, Background in demand forecasting, Background in fulfillment network analytics, Writing 1-2 page narratives

What You'll Do.

Scope complex analyses

Design complex analyses

Execute complex analyses

Analyze inventory placement

Analyze regional demand patterns

Analyze outbound shipping cost drivers

Build self-serve dashboards

Automate self-serve dashboards

Maintain self-serve dashboards

Write production-grade SQL

Maintain ETL pipelines

Build reusable datasets

Maintain reusable datasets

Find improvement opportunities

Frame business problems

Run controlled experiments

Recommend placement strategy changes

Recommend sourcing policy changes

Recommend network design changes

Own metric definition

Investigate variances

Investigate performance misses

Present findings to leadership

Identify manual workflows

Identify repetitive workflows

How You'll Work.

Team & Collaboration

Partner with Program Managers; Partner with Operations; Partner with Supply Chain; Partner with Tech teams; Partner with Category teams

Communication Scope

Data-backed narratives; Verbal reviews

Full 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 op

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