Live opening · Posted 11 days ago

Data Scientist

Tata Consultancy Services Limited · Bengaluru, Karnataka, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 11 days ago
CompanyTata Consultancy Services Limited
LocationBengaluru, Karnataka, India (On-site)
Work modeNo
SourceLinkedin
Listed11 days ago

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About the role

Description supplied by the original job listing.

Greetings from TCS!
We are looking for - Data Scientist ( Data Scientist + Python + ML Ops)
Experience: 6+ Years
Location: Delhi, Pune, Bangalore, Hyderabad
Topic of Evaluation / Skills*
Mandatory
Python
Machine Learning
Deep Learning
Data Science
LLMS
Azure/AWS
Job Requirements*
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 Generation, and ML algorithms such as Decision Trees, Clustering, Support Vector Machines, Artificial Neural Networks, LSTM, CNN, and YOLO, with awareness of their practical advantages and limitations.
Motivated by continuous learning and mastery of emerging technologies and methodologies in the fields of artificial intelligence and machine learning.
Key Responsibilities*
Lead end to end design, development, and deployment of ML/DL solutions for complex business and industrial problems involving structured, time series, and unstructured data.
Define modeling strategies and technical approaches, selecting appropriate ML, DL, Computer Vision, Optimization, and LLM techniques based on problem constraints and business impact.
Oversee data science lifecycle governance, including data acquisition, exploratory analysis, feature engineering, model validation, and performance monitoring.
Drive production grade deployment through MLOps, ensuring scalable, secure, and reliable model operations on cloud platforms such as Azure and AWS.
Lead development of advanced analytics and optimization solutions, translating business objectives into prescriptive and decision support models.
Provide technical leadership and mentoring to data science teams, establishing best practices in Python engineering, experimentation, and model reliability.
Collaborate with stakeholders to translate business needs into AI solutions, clearly communicating assumptions, risks, outcomes, and measurable value.
Continuously evaluate emerging AI/ML and LLM technologies, driving innovation, POCs, and capability building aligned with organizational strategy.

Work arrangement
No

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