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Associate - Data ML Engineer About us Bain & Company is a global consultancy that helps the worlds most ambitious change makers define the future. Across 65 offices in 40 countries, we work alongside our clients as one team with a shared ambition to achieve extraordinary results, outperform the competition and redefine industries. Since our founding in 1973, we have measured our success by the success of our clients, and we proudly maintain the highest level of client advocacy in the industry. In 2004, the firm established its presence in the Indian market by opening the Bain Capability Center (BCC) in New Delhi. The BCC is now known as BCN (Bain Capability Network) with its nodes across various geographies. BCN is an integral and largest unit of (ECD) Expert Client Delivery. ECD plays a critical role as it adds value to Bain's case teams globally by supporting them with analytics and research solutioning across all industries, specific domains for corporate cases, client development, private equity diligence or Bain intellectual property. The BCN comprises of Consulting Services, Knowledge Services and Shared Services. About you / Bachelors or Masters degree in Computer Science, Engineering, Data Science, or related technical fields. / 25 years of experience in data engineering, ML engineering, or full-stack development roles. / Strong programming skills in Python and SQL, with experience building data pipelines and backend services. / Hands-on experience with machine learning model integration and deployment in production environments. / Experience developing backend APIs using frameworks such as FastAPI, Flask, or Django. / Exposure to frontend technologies (e.g., React, NextJs or similar) to build user-facing applications and dashboards. / Experience working with cloud platforms (AWS/Azure/GCP) and contemporary data architectures (data lakes, warehouses). / Familiarity with CI/CD pipelines, Docker, and version control (Git). / Understanding of data modeling, ETL processes, and scalable system design. / Ability to work across the stackfrom data pipelines to APIs to front-end interfaces. / Good-to-have: Proficiency in Excel and PowerPoint with ability to support business communication and storytelling. / Good-to-have: Prior exposure to consulting, analytics use cases, or Consumer Products domain. Who you will work with The Consumer Products Center of Expertise collaborates with Bains global Consumer Products Practice leadership, client-facing Bain leadership and teams, and with end clients on development and delivery of Bains proprietary CP products and solutions. These solutions aim to answer strategic questions of Bains CP clients relating to brand strategy (consumer needs, assortment, pricing, distribution), revenue growth management (pricing strategy, promotions, profit pools, trade terms), negotiation strategy with key retailers, optimization of COGS etc. You will work as part of the team in CP CoE comprising of a mix of Director, Managers, Projects Leads, Associates and Analysts working to implement cloud-based end-to-end advanced analytics solutions. Delivery models on projects vary from working as part of a CP Center of Expertise, broader global Bain case team within the CP ringfence, or within other industry CoEs such as FS / Retail / TMT / Energy / CME / etc with BCN on need basis. What youll do / Build and maintain scalable data pipelines and data processing workflows to support analytics and machine learning use cases. / Develop and deploy machine learning models into production systems, ensuring reliability and scalability. / Design and implement backend APIs to serve data products and ML outputs to downstream applications. / Develop lightweight frontend applications, dashboards, or interfaces to enable business users to interact with data and models. / Collaborate with data scientists to productionize models and integrate them into end-to-end solutions. / Work with large-scale datasets across cloud-based data platforms and warehouses (e.g., Snowflake, Azure Synapse). / Implement best practices in software engineering, including modular code design, testing, and version control. / Utilize containerization (Docker) and CI/CD pipelines for productive deployment and scaling of applications. / Optimize performance of data pipelines, APIs, and user-facing applications. / Translate business requirements into technical solutions and support stakeholders with data-driven tools and insights. What youll do / The AS is expected to have a knack for seeking out challenging problems and producing their own ideas, which they will be encouraged to brainstorm with their peers and managers. They should be willing to learn new techniques and be open to solving problems with an interdisciplinary approach. They must have excellent coding skills and should demonstrate a willingness to write modular, reusable, and functional code. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.