Description:

Bain & Company is hiring a full-stack Associate Data ML Engineer for its Consumer Products Center of Expertise (CP CoE) within the Bain Capability Network (BCN) in New Delhi. In this multi-disciplinary engineering role, you will bridge the gap between heavy data orchestration, backend API modeling, and front-end dashboard presentation. Rather than just training offline models, you will own the end-to-end lifecycle of Bain's proprietary cloud-based consumer analytics tools—productionizing machine learning code, building scalable ETL pipelines, designing fast REST endpoints using FastAPI/Flask, and drafting lightweight React/Next.js interfaces. Your solutions will directly power strategic global consulting case teams addressing multi-million dollar client challenges in brand strategy, revenue growth management, and retail pricing optimization.

Key Technical Skills:

Python, SQL, Machine Learning Model Deployment, REST APIs (FastAPI, Flask, Django), Frontend Frameworks (React, Next.js), Cloud Platforms (AWS/Azure/GCP), Data Warehouses (Snowflake, Azure Synapse), ETL/ELT Pipelines, Docker, CI/CD, Git, Data Modeling

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related quantitative technical field.
• 2 to 5 years of professional experience across data engineering, ML engineering, or full-stack software development roles.
• Strong programming skills in Python and SQL with verified hands-on experience integrating and deploying machine learning models into live, scalable production environments.
• Proven experience developing robust backend APIs using web frameworks like FastAPI, Flask, or Django to serve raw data products and ML inference outputs.
• Tactical exposure to frontend technology stacks (such as React or Next.js) to build interactive data visualizations and business user interfaces.
• Practical familiarity navigating public cloud ecosystems (AWS, Azure, or GCP) alongside modern cloud data warehouses like Snowflake or Azure Synapse.
• Foundational knowledge of software engineering best practices, including version control via Git, modular code design, automated unit testing, containerization using Docker, and continuous integration (CI/CD) pipelines.
• Prior exposure to management consulting, retail/consumer products analytics use cases, and functional business communication tools (Advanced Excel, PowerPoint storytelling).