Lead Data Scientist

Key Responsibilities • Design, build, and deploy scalable AI and Machine Learning models to solve complex business problems. • Develop predictive, classification, recommendation, and optimization models using structured and unstructured data. • Build and fine-tune Large Language Models (LLMs) and Generative AI applications for enterprise use cases. • Develop Retrieval-Augmented Generation (RAG) solutions and prompt engineering strategies. • Collaborate with cross-functional teams including business stakeholders, data engineers, and application developers to deliver AI-driven solutions. • Evaluate model performance and continuously optimize models for accuracy, scalability, and reliability. • Stay current with emerging AI technologies, research, and industry best practices. • Document models, methodologies, and deployment processes following enterprise standards. • Mentor junior data scientists and contribute to AI best practices within the team. Required Qualifications • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field. • 6+ years of experience as a Data Scientist or in a similar AI/ML role. • Strong hands-on experience in Artificial Intelligence and Machine Learning model development. • Experience building, training, validating, and deploying ML models in production environments. • Hands-on experience with Large Language Models (LLMs) and Generative AI technologies. • Experience with prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG). • Strong programming skills in Python. • Experience with ML libraries and frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar. • Experience with SQL and data manipulation techniques. • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud. • Strong analytical, problem-solving, and communication skills. Originally posted on Himalayas