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Lead Data Scientist - Generative AI

NR Consulting
8 - 10 Years
Bangalore

Posted on: 13/05/2026

Job Description

Description :

- Experience : 8+ Years.

- Job Opportunity : Full Time (Permanent).

- Location Remote.

- Interview Process

- Internal Technical Round 1.

- Client Round Virtual 2.

Job Description : Lead Data Scientist Generative AI & Agentic Systems.

Role Overview :

We are seeking a highly skilled Lead Data Scientist with deep expertise (8+ years) in Generative AI, Agentic Systems, and advanced analytics to drive the design and deployment of enterprise-grade AI solutions.

This role combines hands-on engineering, architectural leadership, and product thinking to build scalable AI systems aligned with business outcomes.

Key Responsibilities :


- Lead the design and implementation of Generative AI and multi-agent systems, traditional ML for enterprise use cases.

- Architect and deploy Agentic RAG pipelines, tool-calling frameworks, MCP-based AI systems, regression/classification algorithm based solutions.

- Drive end-to-end AI lifecycle: data ingestion, preprocessing, modeling, evaluation, and deployment.

- Collaborate with cross-functional teams to translate business requirements into AI solutions.

- Ensure production readiness, scalability, and performance optimization of AI systems.

Required Skills & Competencies :

Generative AI & Agentic AI :


- Multi-Agent Systems and orchestration frameworks.


- Agentic RAG architectures, tool-calling, and MCP-based systems.

- LLM orchestration across OpenAI, Claude, Gemini, LLaMA.

- Inter-agent communication protocols (A2A, MCP).

Traditional Machine Learning & Advanced Analytics :

- Strong expertise in supervised and unsupervised learning.

- (Regression, Classification, Clustering, Dimensionality Reduction).

- Experience with tree-based models (XGBoost, Random Forest, LightGBM).

- Hands-on with feature engineering, feature selection, and data preprocessing.

- Exposure to deep learning frameworks (CNNs, RNNs, Transformers where applicable).

AI Engineering & Data Science :

- Strong foundation in Machine Learning and Deep Learning.

- Model fine-tuning, evaluation, and performance optimization.

- Statistical analysis, feature engineering, and data modeling.

Platforms & Tools :

- Cloud: GCP/AWS/AZURE.

- Frameworks: LangChain, LlamaIndex, LangGraph, CrewAI, PandasAI.

- Backend & Apps: FastAPI, Streamlit, Docker.

- Databases: Pinecone, ChromaDB, Neo4j, PostgreSQL.

- Developer Tools: GitHub, Copilot.

Soft Skills :


- Strong problem-solving and analytical thinking.

- Excellent communication skills ability to explain complex AI concepts to business stakeholders.

- Product mindset with focus on business impact and usability.

- Ability to lead cross-functional teams and drive alignment.

- High level of ownership and accountability.

- Adaptability in a fast-evolving AI landscape.

- Strong collaboration and stakeholder management skills.

- Mentorship and team development capabilities.

Education & Certifications :


- Bachelors or masters in computer science, Electronics, Data Science, or related field.

- Relevant certifications in Cloud (GCP/Azure) and Generative AI are a plus.

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