Data Scientist  

Responsibilities :

• Collect, process, and clean large datasets from various sources
• Develop and apply statistical models and machine learning algorithms to solve business problems
• Analyze data to extract actionable insights and present findings to stakeholders using visualizations and reports
• Collaborate with engineering and product teams to implement data-driven solutions
• Conduct A/B testing and experimental design to evaluate model and feature performance
• Monitor and optimize model performance over time
• Stay up to date with the latest data science tools, techniques, and industry trends

Requirements :

• Minimum 2-7 years of experience as a Data Scientist or AI Engineer or similar positions [Mandatory]
• Strong proficiency in Python, including experience with relevant libraries (e.g., requests, asyncio, json, langchain, pydantic)
• Hands-on experience with LLM APIs (e.g., OpenAI, Anthropic, Cohere, Mistral, or open-source models via Hugging Face or similar platforms)
• Proficient in prompt engineering techniques, including prompt design, refinement, and optimization for task-specific use cases
• Solid understanding of natural language processing (NLP) concepts and how large language models operate
• Experience integrating LLMs into real-world applications, such as chatbots, RAG (Retrieval-Augmented Generation), summarization tools, or custom AI agents
• Familiarity with frameworks for building LLM-powered applications, such as LangChain, LlamaIndex, or similar
• Understanding of tokenization, embeddings, context windows, and prompt length limitations in LLMs
• Experience working with vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma) for semantic search or RAG use cases
• Comfortable working with APIs and building backend services to support AI features
• Knowledge of software engineering best practices: version control (Git), testing, documentation, and CI/CD is a plus
• Exposure to MLOps or LLMOps concepts and tools is beneficial
• Ability to rapidly prototype, iterate, and scale LLM-based solutions efficiently
• Strong analytical thinking and problem-solving abilities
• Excellent communication and collaboration skills, with the ability to work in cross-functional teams