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Senior Data Scientist

Shell
Bangalore RMZ-ECO WORLD; SHELL CENTRE – CHENNAI; India Posted Jul 30, 2026
On-site

About this role

Senior Data Scientist

locations

Bangalore RMZ-ECO WORLD

SHELL CENTRE – CHENNAI

time type

Full time

posted on

Posted 2 Days Ago

job requisition id

R206516 , India

Job Family Group: Research and Development

Worker Type: Regular

Posting Start Date: July 30, 2026

Business Unit: Finance

Experience Level: Experienced Professionals

Job Description:

What’s the role

This is a senior individual contributor (IC) role operating as the technical leader for AI and Data Science engineering within the NFR Data Science team. The role is responsible for driving technical excellence, establishing best practices, defining solution architectures, and elevating the team's capability in building, deploying, and scaling enterprise-grade AI solutions. The successful candidate will serve as the team's subject matter expert for Databricks-based AI platforms, MLOps, Agentic AI development, and Databricks Genie solutions. The role is deliberately self-driven and self-defined. The incumbent is expected to proactively identify opportunities, create a pipeline of impactful work, influence without formal authority, and continuously raise the technical maturity of the team through innovation, coaching, standards, and strategic guidance

What you will be doing

AI Engineering Leadership & Best Practices

  • Act as the technical authority for AI Engineering, MLOps, Databricks Genie development, and enterprise AI solution design.
  • Define, implement, and continuously improve AI engineering standards, coding practices, review processes, deployment frameworks, and technical governance.
  • Establish best practices covering:
  • AI architecture design
  • Software engineering standards
  • Testing frameworks
  • Deployment automation
  • Model lifecycle management
  • Documentation standards
  • Production support models
  • Drive adoption of reusable frameworks, accelerators, templates, and reference implementations.
  • Conduct architecture reviews and provide technical guidance across AI and data science initiatives.

Databricks Genie & Agentic AI Leadership

  • Design, develop, and deploy enterprise-grade Databricks Genie solutions for business stakeholders across markets.
  • Own the reference architecture for Genie-based solutions.
  • Define best practices for:
  • Semantic model design
  • Prompt engineering
  • Response evaluation
  • Accuracy optimization
  • Cost optimization
  • Security and governance
  • Lead the adoption of Agentic AI capabilities including:
  • Multi-agent systems
  • AI workflow orchestration
  • Tool usage patterns
  • Retrieval-augmented generation (RAG)
  • Human-in-the-loop architectures
  • Establish scalable development patterns that enable faster and more consistent delivery of GenAI solutions.

MLOps & Solution Engineering

  • Lead implementation and continuous improvement of MLOps practices across the team.
  • Define standards for:
  • Source code management, CI/CD pipelines
  • Automated testing, Model versioning
  • Mon

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