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Job Title: Data Scientist Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry. Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services. #Capco has a tolerant, open culture that values diversity, inclusivity, and creativity. CAREER ADVANCEMENT With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands. DIVERSITY & INCLUSION We believe that diversity of people and perspective gives us a competitive advantage. Design, develop, and deploy end-to-end machine learning solutions using Python and Databricks. Build and optimize scalable data processing pipelines using PySpark and Spark. Perform data extraction, cleansing, transformation, and feature engineering on structured and unstructured datasets. Develop, evaluate, and implement traditional machine learning models for classification, regression, clustering, and prediction problems. Develop reusable, production-ready ML workflows and analytical frameworks. Collaborate with data engineers and business stakeholders to understand business requirements and translate them into scalable analytical solutions. Optimize model performance through experimentation, hyperparameter tuning, and validation. Ensure data quality, governance, and best practices throughout the data and model lifecycle. Document methodologies, model performance, and technical solutions for knowledge sharing and maintainability. Programming Python SQL Data Science & Machine Learning Strong understanding of traditional Machine Learning algorithms Statistical Analysis Data Preprocessing and Transformation Big Data & Data Processing Large-scale data processing Data pipeline development and optimization ETL/ELT concepts Strong hands-on experience with Databricks Experience working with Databricks Notebooks Building scalable ML workflows in Databricks Python Libraries Cloud & Platform Azure Data Services (preferred) Azure Machine Learning (good to have) CI/CD concepts for ML pipelines (preferred) Experience implementing MLOps pipelines using MLflow or Azure ML. Explainable AI frameworks such as SHAP or LIME. Experience with orchestration tools such as Azure Data Factory or Apache Airflow. Experience with Delta Lake and Unity Catalog. Knowledge of Docker and containerized deployments. Experience working in Agile environments. Preferred Experience 3+ years of experience in Data Science and Machine Learning.Strong experience implementing ML solutions on Databricks.Experience building production-grade data and ML pipelines using PySpark.Experience with Azure cloud ecosystem is preferred.Experience in Energy, Utilities, Manufacturing, or other data-intensive industries is an advantage If you are keen to join us, you will be part of an organization that values your contributions, recognizes your potential, and provides ample opportunities for growth. For more information, visit Follow us on Twitter, Facebook, LinkedIn, and YouTube. .
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.