Data Scientist

We are Hiring.

Please share your updated resume at [email removed] if you are interested.

About the Role

The design and development of a cutting-edge application powered by large language models (LLMs). This tool will provide market analysis and generate high-quality, data-driven periodic insights. You will play a critical role in building a scalable and intelligent system that integrates structured data, NLP capabilities, and domain-specific knowledge to produce analyst-grade content.

Key Responsibilities

• Design and develop LLM-based systems for automated market analysis.
• Build data pipelines to ingest, clean, and structure data from multiple sources (e.g., market feeds, news articles, technical reports, internal datasets).
• Fine-tune or prompt-engineer LLMs (e.g., GPT-4.5, Llama, Mistral) to generate concise, insightful reports.
• Collaborate closely with domain experts to integrate industry-specific context and validation into model outputs.
• Implement robust evaluation metrics and monitoring systems to ensure quality, relevance, and accuracy of generated insights.
• Develop and maintain APIs and/or user interfaces to enable analysts or clients to interact with the LLM system.
• Stay up to date with advancements in the GenAI ecosystem and recommend relevant improvements or integrations.
• Participate in code reviews, experimentation pipelines, and collaborative research discussions.

Qualifications Required:

• Strong fundamentals in machine learning, and natural language processing (NLP).
• Good Understanding of Database Concepts and hands on experience on SQL Query.
• Proficiency in Python, with hands-on experience using libraries such as NumPy, Pandas, and Matplotlib/Seaborn for data analysis and visualization & OOPs Concepts.
• Experience developing applications using LLMs (both closed- and open-source models). Familiarity with frameworks like Hugging Face, LangChain,etc.
• Web Scrapping/ Ground Search
• Experience working with REST APIs, data ingestion pipelines, and automation workflows.
• Knowledge of prompt engineering, Retrieval-Augmented Generation (RAG), and LLM evaluation strategies.
• Strong analytical thinking, problem-solving skills, and the ability to convert complex technical work into business-relevant insights.

Good To Have:

• Familiarity with the chemical or energy industry, or prior experience in market research/analyst workflows.
• Exposure to frameworks such as OpenAI Agentic SDK, etc.
• Experience deploying ML/LLM solutions to production environments (Docker, CI/CD).