Data Scientist

Job Description:

We are looking for an experienced Data Scientist with strong AI, Machine Learning, and LLM expertise to develop intelligent data-driven solutions and AI applications. The ideal candidate should have strong hands-on experience with Python, machine learning, NLP, Generative AI, and Large Language Models.

Key Responsibilities:

• Develop and deploy machine learning and AI models using Python.
• Build LLM and Generative AI solutions for enterprise use cases.
• Work with OpenAI, Azure OpenAI, Claude, Gemini, or similar LLM platforms.
• Develop RAG (Retrieval-Augmented Generation) applications using embeddings and vector databases.
• Perform prompt engineering, model evaluation, fine-tuning, and optimization.
• Apply NLP techniques for text classification, summarization, extraction, and semantic search.
• Build data pipelines for data preparation, feature engineering, and model training.
• Analyze large datasets and identify meaningful business insights.
• Develop and evaluate ML/AI models using appropriate performance metrics.
• Work with Python, Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.
• Collaborate with Data Engineers, Software Engineers, and business stakeholders to deploy AI solutions.
• Implement AI models and applications in cloud environments such as AWS, Azure, or Google Cloud Platform.
• Monitor model performance and continuously improve AI/ML solutions.

Required Skills:

• Strong experience in Data Science and Machine Learning.
• Advanced Python programming skills.
• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Experience with RAG, embeddings, vector databases, and prompt engineering.
• Strong knowledge of NLP and Natural Language Processing techniques.
• Experience with OpenAI / Azure OpenAI / Claude / Gemini or similar LLM APIs.
• Experience with Scikit-learn, Pandas, NumPy, and preferably TensorFlow/PyTorch.
• Strong understanding of statistics, machine learning algorithms, and model evaluation.
• Experience working with SQL and large datasets.
• Exposure to AWS, Azure, or Google Cloud Platform.

Preferred Skills:

• Experience with LangChain, LlamaIndex, Hugging Face, or similar AI frameworks.
• Experience with FAISS, Pinecone, Weaviate, Chroma, or other vector databases.
• Experience with LLM fine-tuning and evaluation frameworks.
• Experience deploying AI/ML models using Docker, Kubernetes, or MLflow.
• Experience in enterprise AI/GenAI implementations.