Data Analyst

Birlasoft is looking for a Data Analyst with hands-on experience in real-world data science and analytics projects. The role involves applying Machine Learning, Statistical Analysis, Deep Learning, Computer Vision and Natural Language Processing (NLP) techniques to solve business problems across multiple industries. The candidate will work with data and analytics teams to develop, test, evaluate and monitor analytical and machine learning solutions. The role requires strong fundamentals in data science, programming and statistical modelling, along with the ability to learn and adapt to evolving AI and analytics technologies. The role may involve working across domains such as Manufacturing, Life Sciences, Finance and Retail, and business functions including Operations, Sales, Finance, IT and HR. ### Key Responsibilities Analyze business problems and identify suitable data-driven solutions. Apply Machine Learning and Data Science techniques to real-world business problems. Develop and evaluate statistical and machine learning models. Work with techniques including statistical ML, Deep Learning, Computer Vision and NLP. Perform model testing and validation. Analyze model performance using evidence-based and statistical approaches. Monitor deployed solutions after they go live. Identify opportunities to improve model performance and reliability. Work with Python and R for data analysis and model development. Prepare and process datasets for analytical and machine learning use cases. Collaborate with data engineers, architects and deployment teams. Assist with API creation and deployment of analytical solutions where required. Support containerization of applications using Docker. Work with Azure and Databricks-based data and analytics environments. Apply appropriate statistical techniques to solve business problems. Maintain coding standards and development best practices. Troubleshoot data and model-related issues. Communicate analytical findings and technical approaches to team members and stakeholders. Work effectively in an Agile environment. ### Requirements 1–3 years of professional experience in Data Analytics, Data Science or a related field. Bachelor's or Master's degree in Computer Engineering, Computer Science, Data Science or another relevant STEM field. Strong programming knowledge in Python and/or R. Strong understanding of Machine Learning concepts and techniques. Knowledge of statistical Machine Learning techniques. Understanding of Deep Learning concepts. Knowledge of Computer Vision and NLP. Experience with model testing and validation. Ability to analyze and evaluate model performance using statistical methods. Understanding of data preprocessing and analysis techniques. Working knowledge of SQL and relational database systems. Experience working with Azure-based data/analytics platforms is preferred. Knowledge of Databricks is preferred. Understanding of API development and deployment is an advantage. Exposure to Docker/containerization is preferred. Ability to work with large datasets and complex business problems. Strong analytical and problem-solving skills. Good understanding of software development and coding standards. Good communication and teamwork skills. Ability to learn and adapt to new AI and Data Science technologies. Ability to work in an Agile environment. Ability to collaborate with architects, data engineers and deployment teams.