Data Scientist

Role & responsibilities

• Build and deploy machine learning models for prediction, recommendation, and optimization use cases.
• Design end-to-end ML pipelines including feature engineering, model training, validation, and monitoring.
• Develop Generative AI solutions using LLMs for insight generation, conversational interfaces, and automation.
• Implement RAG pipelines using vector stores and semantic retrieval.
• Design agentic workflows where AI systems autonomously reason, plan, and use tools.
• Collaborate with product and engineering teams to translate business problems into scalable AI solutions.
• Monitor model performance and drive continual improvement.

Preferred candidate profile

• 5+ years of experience in Data Science / Machine Learning.
• Strong programming proficiency in Python with ML ecosystem libraries (NumPy, pandas, scikit-learn, PyTorch or TensorFlow).
• Hands-on experience building production-grade ML models and deploying them into scalable environments.
• Good understanding of statistical learning concepts and model interpretability.
• Exposure to Generative AI systems, LLM APIs, prompt engineering, or RAG architectures.
• Familiarity with agent-based AI frameworks and workflow orchestration concepts.
• Ability to work in fast-paced environments and collaborate across analytics, engineering, and business teams.