ML Data Associate I

Amazon's interview process typically starts with an online assessment that tests coding efficiency and logical reasoning, followed by one or two technical rounds focusing on data structures, algorithms, and domain‑specific knowledge like machine learning concepts. The final HR round evaluates cultural fit through behavioral questions based on Amazon's Leadership Principles. Preparation should emphasize problem‑solving speed, clear communication, and real‑world examples of ownership and customer obsession.

Amazon promotes a high‑performance culture built on its Leadership Principles, encouraging ownership, customer obsession, and continuous learning. Employees enjoy clear growth pathways, exposure to large‑scale projects, and a collaborative environment, though the pace can be demanding. Work‑life balance is supported through flexible work arrangements and a strong focus on results rather than hours logged.

Bachelor's or Master's degree in Computer Science, Information Technology, Electronics, Mathematics, Statistics or related fields; Minimum 60% aggregate (or CGPA 6.0/10); Graduation batch 2024‑2026; No active backlogs at the time of application; Strong analytical and problem‑solving abilities; Good communication skills in English.

Round 1: Online Assessment (coding + logical reasoning) → Round 2: Technical Interview (ML concepts, data handling, coding) → Round 3: HR Interview (behavioral, cultural fit)

Amazon, a global e‑commerce and cloud‑computing giant, has built its reputation on relentless customer obsession, innovation at scale, and a culture of ownership. In India, Amazon operates massive fulfillment centers, a thriving marketplace, and AWS data‑center infrastructure, employing hundreds of thousands of talent across technology, operations, and business functions. The company’s commitment to long‑term growth, sustainability, and up‑skilling its workforce makes it a top destination for fresh graduates who want to work on real‑world problems that impact millions of customers daily. The role of ML Data Associate I is designed for recent graduates with a strong analytical mindset and a passion for machine learning. As a member of the data science and analytics team, you will support the end‑to‑end lifecycle of data‑driven solutions, from data ingestion and cleaning to model evaluation and deployment. You will work closely with senior data scientists, product managers, and engineering teams to translate business requirements into actionable insights and scalable ML pipelines. Key Responsibilities: 1. Collect, clean, and preprocess large‑scale structured and unstructured datasets from internal Amazon systems. 2. Perform exploratory data analysis to uncover trends, anomalies, and opportunities for model improvement. 3. Build, train, and validate machine‑learning models using Python libraries such as scikit‑learn, TensorFlow, or PyTorch. 4. Develop and maintain data pipelines on AWS services (S3, Glue, Lambda) to ensure reliable data flow. 5. Create visual dashboards and reports using Tableau or QuickSight to communicate findings to stakeholders. 6. Conduct A/B testing and statistical validation to measure model performance in production. 7. Document code, methodologies, and results following Amazon’s best‑practice guidelines. 8. Collaborate with cross‑functional teams to integrate ML solutions into existing Amazon products and services. 9. Stay updated with the latest research in machine learning, data engineering, and cloud technologies. 10. Participate in knowledge‑sharing sessions and contribute to the continuous improvement of the analytics community. Tech Stack: Python, SQL, Pandas, NumPy, scikit‑learn, TensorFlow/PyTorch, AWS (S3, Glue, Lambda, SageMaker), Tableau/QuickSight, Git, Linux. Growth Path: Starting as an ML Data Associate, high performers can progress to Data Scientist, Senior Data Scientist, and eventually to Machine Learning Engineer or Product Owner roles, with opportunities to lead large‑scale AI initiatives across Amazon’s diverse business units. Why Join Amazon? You will be part of a fast‑moving environment where data‑driven decisions shape the future of retail and cloud services. Amazon offers a competitive compensation package, robust learning resources, and a culture that encourages ownership, bias for action, and continuous improvement. Fresh talent gets exposure to cutting‑edge technologies, mentorship from industry leaders, and the chance to make an impact at a company that values innovation above all else.