Senior Data Scientist

Tata Consultancy Services Limited; Dadri, Bengaluru, Delhi; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

Tata Consultancy Services Limited in Pan India seeks a Senior Data Scientist to lead design, development, and deployment of advanced data-driven solutions leveraging cutting-edge AI/ML and Generative AI technologies. The role requires deep expertise in data profiling, data analysis, ML algorithms, and GenAI applications to solve complex business challenges.

You will architect robust data science solutions, guide technical teams, and drive innovation across enterprise analytics and AI

Qualifications

• 12+ years of IT experience with 5+ years in data science, AI/ML, or advanced analytics roles.
• Proven hands-on experience designing and deploying AI/ML solutions.
• Experience with data profiling, cleansing, and exploratory data analysis.

Responsibilities

• Lead end-to-end design and implementation of data science solutions for enterprise applications.
• Develop, validate, and deploy AI/ML models using Python, R, and modern ML frameworks.
• Design and implement Generative AI solutions (LLMs, RAG, AI agents) for enterprise use cases.
• Architect and optimize data pipelines for model training, evaluation, and deployment.

Skills

Data profiling

Data analysis

Machine learning algorithms

GenAI models

AI/ML deployment

Leadership

Stakeholder communication

MLOps

Tools

Pandas

SQL

Power BI

scikit-learn

TensorFlow

PyTorch

OpenAI

Azure AI

AWS SageMaker

Python

R

Git

Job description

Job Description: Senior Data Scientist AI/ML & GenAI

Experence:5-12

Loc:Pan India

We are seeking a highly experienced Senior Data Scientist to lead the design, development, and deployment of advanced data-driven solutions leveraging cutting-edge AI/ML and Generative AI technologies. This role demands deep expertise in data profiling, data analysis, machine learning algorithms, and the practical application of GenAI models to solve complex business challenges.

You will be responsible for architecting robust data science solutions, guiding technical teams, and driving innovation across enterprise-scale analytics and AI initiatives. The role also involves collaborating with stakeholders, defining strategic data science roadmaps, and ensuring alignment with industry best practices and enterprise governance standards.

Responsibilities

• Lead the end-to-end design and implementation of data science solutions for business-critical applications, ensuring scalability, performance, and compliance.
• Conduct advanced data profiling, cleansing, and exploratory data analysis to uncover actionable insights and inform model development.
• Develop, validate, and deploy AI/ML models (including supervised, unsupervised, and deep learning algorithms) using Python, R, and modern ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Design and implement Generative AI solutions (e.g., LLMs, RAG, AI agents) for enterprise use cases, leveraging platforms such as OpenAI, Azure AI, or AWS SageMaker.
• Champion data governance, responsible AI principles, and model interpretability, ensuring solutions are ethical, transparent, and compliant with regulatory standards.
• Collaborate with cross-functional teams (business, engineering, product, and leadership) to gather requirements and translate business needs into technical solutions and strategic data science roadmaps.
• Provide technical leadership and mentorship across data science projects, conducting design reviews and enforcing development standards.
• Architect and optimize data pipelines for model training, evaluation, and deployment, integrating with core business systems and cloud platforms.
• Develop and maintain documentation for data science workflows, model architectures, and integration patterns.
• Stay current with emerging trends in AI/ML, GenAI, and data engineering, acting as a subject matter expert and driving continuous innovation.

Required Qualifications

• 12+ years of overall IT experience, with 5+ years in data science, AI/ML, or advanced analytics roles.
• Proven, hands-on experience designing and deploying solutions using:
• - Data profiling and analysis tools (e.g., Pandas, SQL, Power BI)
• - Machine learning frameworks (scikit-learn, TensorFlow, PyTorch)
• - Generative AI platforms (OpenAI, Azure AI, AWS SageMaker)
• - Python and R for data science and ML
• Strong understanding of machine learning algorithms, model lifecycle management, and MLOps best practices.
• Demonstrable experience in designing data governance, data strategy, and responsible AI frameworks.
• Deep knowledge of cloud-native architecture and data engineering (Azure, AWS, or GCP).
• Experience with data pipelines, feature engineering, and model deployment in production environments.
• Familiarity with CI/CD, version control (Git), and Agile delivery models.
• Excellent communication and presentation skills, with the ability to present complex ideas to technical and non-technical audiences.