Lead Data Scientist

Egon Zehnder; Gurugram District; Hybrid; INR 4,500,000 - 7,500,000; Full time

Job summary

Egon Zehnder is seeking an accomplished Senior Data Scientist to design and deploy ML models, focusing on NLP, GenAI, and RAG-based AI solutions. You will collaborate with data engineers to scale data pipelines, lead feature engineering efforts, and mentor junior data scientists in a global consulting environment.

The role requires deep expertise in Python, ML libraries, and cloud ML tooling, with a strong background in CS fundamentals and a track record of delivering enterprise-grade AI

Qualifications

• 10+ years of experience in data science, ML, and AI.
• Master's or PhD in CS, Statistics, Mathematics, or related field.
• Proficiency in Python, SQL, and ML libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face).
• Experience with NLP and GenAI tools (Azure Foundry, GPT, LangChain).
• Hands-on experience with RAG systems and vector databases.
• Familiarity with Azure, AWS, GCP and MLOps tools (MLflow, Airflow, Kubeflow).
• Strong CS fundamentals; data structures and algorithms.
• Experience with Azure Copilot Studio and Cognitive Services.
• Azure Foundry experience is a strong plus.

Responsibilities

• Design, develop, and deploy ML models using classical algorithms and deep learning.
• Build NLP solutions for text classification, entity recognition, summarization, and conversational AI.
• Develop and fine-tune GenAI models for content generation, code synthesis, and personalization.
• Architect and implement Retrieval-Augmented Generation (RAG) systems.
• Collaborate with data engineers to build scalable data pipelines and feature stores.
• Perform advanced feature engineering to improve model accuracy and robustness.
• Work with large-scale datasets using distributed computing frameworks.
• Translate business problems into data science solutions and communicate findings.
• Present insights through storytelling and visualization.
• Mentor junior data scientists and contribute to knowledge sharing.

Skills

Python

SQL

ML libraries

NLP

GenAI tools

RAG systems

Vector databases

Azure

AWS / GCP

MLOps

Data structures

Azure Copilot

Azure Cognitive

Azure Foundry

LLM fine-tuning

GenAI safety

Education

Masters or PhD in CS/Statistics/Math

Tools

Azure AI Foundry

Azure AI Studio

GPT

LLaMA

LangChain

Hugging Face

TensorFlow

PyTorch

scikit-learn

Job description

Role & responsibilities

Key Responsibilities

• Design, develop, and deploy ML models using classical algorithms (e.g., regression, decision trees, ensemble methods) and deep learning architectures (CNNs, RNNs, Transformers).
• Build NLP solutions for tasks such as text classification, entity recognition, summarization, and conversational AI.
• Develop and fine-tune GenAI models for use cases like content generation, code synthesis, and personalization.
• Architect and implement Retrieval-Augmented Generation (RAG) systems for enhanced contextual AI applications.
• Collaborate with data engineers to build scalable data pipelines and feature stores.
• Perform advanced feature engineering and selection to improve model accuracy and robustness.
• Work with large-scale structured and unstructured datasets using distributed computing frameworks.
• Translate business problems into data science solutions and communicate findings to stakeholders.
• Present insights and recommendations through compelling storytelling and visualization.
• Mentor junior data scientists and contribute to internal knowledge sharing and innovation.

Preferred candidate profile

• 10+ years of experience in data science, machine learning, and AI.
• Strong academic background in Computer Science, Statistics, Mathematics, or related field (Masters or PhD preferred).
• Proficiency in Python, SQL, and ML libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face).
• Experience with NLP and GenAI tools (e.g., Azure AI Foundry, Azure AI studio, GPT, LLaMA, LangChain).
• Hands-on experience with Retrieval-Augmented Generation (RAG) systems and vector databases.
• Familiarity with cloud platforms (Azure preferred, AWS/GCP acceptable) and MLOps tools (MLflow, Airflow, Kubeflow).
• Solid understanding of data structures, algorithms, and software engineering principles.
• Experience with Aure, Azure Copilot Studio, Azure Cognitive Services
• Experience with Azure AI Foundry would be a strong added advantage

Preferred Skills

• Exposure to LLM fine-tuning, prompt engineering, and GenAI safety frameworks.
• Experience in domains such as consulting, finance, healthcare, retail, or enterprise SaaS.
• Contributions to open-source projects, publications, or patents in AI/ML.

Soft Skills

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder engagement abilities.
• Ability to work independently and collaboratively in cross-functional teams.
• Passion for continuous learning and innovation.