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