Data Analyst

The interview experience at Amazon Wood typically starts with an online aptitude test focusing on data interpretation and logical reasoning. Successful candidates move to a technical round where they solve SQL queries and Python data‑manipulation tasks, followed by a managerial interview that assesses problem‑solving approach and business acumen. The final HR round discusses cultural fit and compensation. Preparation should emphasize Amazon's leadership principles and real‑world analytics scenarios.

Amazon Wood promotes a data‑first culture where every decision is backed by metrics. Employees enjoy rapid career growth, mentorship programs, and a balance between high‑impact projects and personal development. The company encourages work‑life harmony through flexible timings and remote‑friendly policies while maintaining a collaborative office environment.

Graduation in B.Tech/B.E., B.Sc or B.Com with a focus on Statistics, Mathematics, Computer Science, Information Technology or related fields. Minimum 60% aggregate (or CGPA 6.0/10). Final year students of the 2025 or 2026 batch are eligible. No active backlogs at the time of joining. Strong analytical mindset and willingness to learn are essential.

Round 1: Online Assessment (aptitude, data interpretation) → Round 2: Technical Interview (SQL/Python case studies) → Round 3: Managerial Interview → Round 4: HR (based on company knowledge)

Amazon Wood, a subsidiary of the global e‑commerce giant Amazon, operates a suite of seller services that enable millions of merchants to list, sell, and fulfill products on the Amazon marketplace. The company’s Bengaluru office serves as a hub for analytics, product development, and seller‑centric operations, fostering a fast‑paced environment where data‑driven decisions shape the experience of both sellers and buyers. With a strong emphasis on innovation, Amazon Wood invests heavily in building scalable tools and platforms that simplify seller reimbursements, performance tracking, and dispute resolution. The work culture blends Amazon’s leadership principles with a local focus on collaboration, continuous learning, and customer obsession. The Data Analyst role is positioned at the intersection of business operations and technology. As a fresher, you will be responsible for translating raw data from Amazon’s seller services into actionable insights that improve seller performance and reduce friction in the reimbursement workflow. You will partner closely with account managers, product owners, and engineering teams to identify problem areas, design metrics, and recommend data‑backed solutions. This role offers exposure to end‑to‑end analytics pipelines, from data extraction using SQL and Python to visualization in Tableau or QuickSight, and ultimately influencing strategic decisions that impact revenue and seller satisfaction. Key responsibilities include: 1. Understanding Amazon Seller Services products and tracking key performance indicators (KPIs) related to reimbursements and seller health. 2. Building and maintaining dashboards that surface trends, anomalies, and problem areas for internal stakeholders. 3. Collaborating with the account management team to investigate seller issues and provide data‑driven recommendations. 4. Using Amazon’s internal tools (Seller Central, Athena, QuickSight) to validate hypotheses and test solutions. 5. Defining new metrics and analytical techniques to continuously improve seller performance. 6. Preparing regular performance reports and presenting findings to senior leadership. 7. Conducting root‑cause analysis for reimbursement discrepancies and proposing corrective actions. 8. Assisting in the development of automated reporting workflows to reduce manual effort. 9. Staying updated with industry best practices in data analytics, statistical modeling, and visualization. 10. Contributing to cross‑functional projects that aim to enhance the overall seller experience. The tech stack typically includes SQL, Python (pandas, numpy), Excel, Tableau/QuickSight, and Amazon‑specific tools such as Athena and Redshift. Growth paths can lead to senior analyst, analytics manager, or product analyst roles, with opportunities to specialize in areas like pricing, logistics, or marketplace strategy. Joining Amazon Wood offers a chance to work on high‑impact problems, gain mentorship from seasoned data professionals, and be part of a culture that rewards curiosity, ownership, and customer focus.