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
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