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.

Lead Data Scientist

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