Data Scientist(Walkin benguluru 12 sep )

Tata Consultancy Services; Bengaluru; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Tata Consultancy Services in Bengaluru seeks an experienced ML Engineer to design, develop, and deploy machine learning and deep learning models for tackling industrial data challenges. You will leverage Python for analytics, implement robust data workflows, and apply NLP/LLMs with retrieval-augmented techniques.

Join a team focusing on scalable ML solutions and cloud deployments using MLOps on Azure/AWS, ensuring production-grade performance and insights for complex datasets.

Qualifications

• Proficient in Python for statistical analysis and ML/DL model development.
• Experience deploying AI/ML solutions with MLOps on Azure and AWS.
• Strong knowledge of NLP, large language models, and retrieval-augmented methods.
• Experience with data workflows: collection, cleaning, feature selection, validation.

Responsibilities

• Design, develop, and deploy ML/DL models for industrial challenges.
• Implement data workflows from collection to model validation.
• Optimize models using algorithms and optimization techniques.
• Deploy AI/ML solutions with MLOps on cloud platforms.

Skills

Python

Machine Learning

Deep Learning

NLP

LLMs

MLOps

Cloud (Azure/AWS)

Tools

Genetic Algorithms

Linear Programming

Quadratic Programming

Azure

AWS

Job description

• Designed, developed, and deployed Machine Learning and Deep Learning models for industrial challenges involving large-scale numerical, categorical, and time series data, as well as images and videos.
• Extensive experience in Python programming for statistical analysis, custom algorithm development, and business insight generation using ML/DL models.
• Proficient in optimization techniques including Genetic Algorithms, Linear and Quadratic Programming, and others
• Skilled in comprehensive data workflows: collection, exploratory analytics, data cleansing, feature selection, and model validation.
• Experience in deploying AI/ML solutions using MLOPs on cloud platforms such as Azure and AWS.

Solid knowledge of NLP, Large Language Models, Retrieval-Augmented