Business Research Analyst - I, RBS Tech

Candidates typically face a three‑stage process: an initial online test focusing on aptitude and basic ML concepts, followed by a technical interview that probes coding ability, model building, and prompt engineering knowledge. The final HR round assesses cultural fit and communication skills. Preparation should include practicing data‑science case studies and reviewing LLM prompt techniques.

RBS Tech promotes a collaborative environment where engineers and analysts work side‑by‑side on high‑impact projects. Employees enjoy a balance of autonomy and mentorship, with clear pathways for skill development and rapid career progression. The company emphasizes work‑life balance through flexible timings and regular wellness initiatives.

Bachelor's degree in a quantitative or STEM discipline (e.g., Computer Science, Engineering, Mathematics, Physics, Statistics). Minimum aggregate of 60% (or CGPA 6.0/10). Fresh graduates from the 2024‑2025 batch are preferred. No active backlogs at the time of joining; a maximum of one backlog allowed if cleared before the joining date.

Round 1: Online assessment (aptitude, logical reasoning, basic ML concepts) → Round 2: Technical interview (coding, ML case studies, prompt design) → Round 3: HR interview (behavioral fit, career aspirations)

RBS Tech is a technology arm of Amazon’s Retail Business Systems (RBS) group, responsible for building and maintaining the data‑driven backbone that powers Amazon’s online catalog, selection, and supply‑chain quality. Operating out of the vibrant tech hub of Bengaluru, the team collaborates closely with product, engineering, and operations stakeholders to ensure that millions of items are accurately represented, competitively priced, and readily available for customers worldwide. The culture emphasizes rapid experimentation, data‑first decision making, and a relentless focus on customer impact, making it an ideal place for fresh talent eager to work on large‑scale, real‑world problems. The Business Research Analyst – I role sits at the intersection of data science, machine learning, and business strategy. As a Level‑4 Research Analyst, you will design, implement, and evaluate both classical machine‑learning models and generative‑AI solutions to address concrete business challenges such as catalog quality prediction, demand forecasting, and recommendation refinement. You will work under the mentorship of senior scientists and engineers, translating ambiguous business questions into concrete analytical experiments and delivering actionable insights that directly influence Amazon’s retail operations. Key responsibilities include: 1. Implement classification, regression, and clustering models using Python and popular ML frameworks (scikit‑learn, XGBoost, PyTorch). 2. Design and iterate prompts for large language models (LLMs) employing few‑shot, chain‑of‑thought, and instruction‑based techniques. 3. Conduct offline evaluation, benchmarking, and performance testing of both ML and LLM outputs against business KPIs. 4. Collaborate with software engineers to package models as services and monitor them in production environments. 5. Document experiment methodology, results, and lessons learned in clear, reproducible reports. 6. Participate actively in sprint planning, model review meetings, and cross‑functional brainstorming sessions. 7. Perform data extraction, cleaning, and feature engineering using SQL and Python libraries (pandas, NumPy). 8. Analyze trade‑offs between generative AI approaches and traditional ML to recommend optimal solutions for specific use‑cases. 9. Assist in building data pipelines and ensuring data quality for downstream analytics. 10. Communicate findings to both technical and non‑technical audiences through visualizations and presentations. Tech stack: Python, SQL, pandas, NumPy, scikit‑learn, XGBoost, PyTorch/TensorFlow, LangChain or similar LLM orchestration tools, AWS SageMaker, Git, Docker, and CI/CD pipelines. Growth path: Starting as a Business Research Analyst, high performers can progress to Senior Analyst, Machine‑Learning Engineer, or Product‑Data Scientist roles, eventually moving into leadership positions such as ML Team Lead or Product Owner within the RBS ecosystem. Why join RBS Tech? You will gain exposure to Amazon‑scale data, work on cutting‑edge AI/GenAI technologies, and see the direct impact of your models on millions of customers. The role offers a blend of research rigor and production focus, mentorship from seasoned scientists, and a clear career ladder in a supportive, innovation‑driven environment.