Lead Data Scientist – Generative AI (GenAI)

Lead Data Scientist – Generative AI (GenAI)

Experience

12–15+ Years (Data Science / AI Experience)

Employment Type

Full-Time (W2 Only)

Location

USA (Hybrid / Onsite)

Work Authorization

H4 EAD, L2S, GC EAD, Green Card, US Citizen

Job Summary

We are seeking a highly accomplished

Lead Data Scientist with strong Generative AI expertise

to design and drive enterprise-scale AI solutions. The ideal candidate will have deep experience in

machine learning, statistical modeling, Large Language Models (LLMs), and advanced analytics

, along with strong leadership capabilities to guide teams and deliver impactful AI-driven products.

This role requires ownership of

GenAI solution design, model development, experimentation, deployment, and performance optimization

across enterprise environments.

Key Responsibilities

• Define and lead

GenAI and data science strategy

across business use cases.

• Design and implement

LLM-based applications including RAG architectures

.

• Lead development of

machine learning models and advanced analytics solutions

.

• Perform deep

exploratory data analysis (EDA)

and derive actionable insights.

• Architect end-to-end

ML pipelines (data ingestion → training → deployment → monitoring)

.

• Optimize models for accuracy, scalability, and cost efficiency.
• Collaborate with Data Engineers, ML Engineers, and Product stakeholders.
• Establish best practices for

MLOps, model governance, and evaluation frameworks

.

• Mentor junior data scientists and lead technical decision-making.
• Drive innovation in

AI/ML and Generative AI solutions

.

Required Technical Skills

Data Science & ML

• Strong expertise in

Machine Learning & Statistical Modeling

• Python (NumPy, Pandas, Scikit-learn)
• Feature engineering, model evaluation, and tuning

Generative AI

• LLMs (OpenAI, Anthropic, LLaMA, etc.)
• Prompt engineering and LLM orchestration
• RAG (Retrieval-Augmented Generation)
• LangChain / LlamaIndex / Hugging Face

Data & Processing

• SQL
• Large-scale data handling and transformation

Cloud & MLOps

• AWS / Azure / GCP
• MLflow / SageMaker / Azure ML
• CI/CD for ML pipelines
• Model deployment and monitoring

Preferred Qualifications

• Experience with Deep Learning (TensorFlow / PyTorch)
• Exposure to vector databases (Pinecone, FAISS, Chroma)
• Experience with Databricks or big data platforms
• Strong leadership, communication, and stakeholder management skills

Eligibility & Compliance

• W2 Full-Time Only
• No C2C
• No consultancy or vendor profiles

How to Apply

📩 Share your updated resume to

[email protected]