Experience: 35 Years Location: Mumbai Employment Type: Full-Time About PhillipCapital India PhillipCapital India is part of the Singapore-based PhillipCapital Group, a global financial powerhouse. We provide a comprehensive suite of financial services, including stock broking, investment advisory, and research. We are looking for a data-driven professional to help us leverage our vast financial datasets to drive innovation and superior client experiences. The Role We are seeking a highly skilled and innovative Data Scientist to work on initiatives in Large Language Models (LLMs) and Generative AI. In this role, you will be the driving force behind building intelligent systems that augment our analysts. You will design, build, and deploy GenAI solutions that automate financial analysis, extract complex insights from unstructured text, and generate draft research reports. If you are passionate about the intersection of cutting-edge AI and high-stakes finance, this is the role for you.
Key Responsibilities
GenAI Solution Architecture: Design and develop end-to-end Generative AI applications tailored for equity research workflows, such as automated earnings summaries, sentiment analysis, and financial Q&A assistants. LLM Fine-Tuning: Fine-tune foundational LLMs (e.g., Llama 3, Mistral, Gemini) on proprietary financial corpora using parameter-efficient techniques (PEFT, LoRA, QLoRA) to improve domain-specific accuracy and reasoning. Prompt Engineering & Tuning: Develop robust, automated prompt management and evaluation systems. Utilize advanced prompt engineering (Few-Shot, Chain-of-Thought, ReAct) to optimize model outputs for financial data extraction and summarization. RAG System Development: Build and scale Retrieval-Augmented Generation (RAG) pipelines that accurately connect our proprietary research and external financial documents with LLMs, ensuring low latency and high relevance. Model Evaluation & Safety: Implement rigorous evaluation frameworks to measure model accuracy, mitigate hallucinations, and ensure outputs meet the strict compliance and reliability standards of the financial industry. Cross-Functional Collaboration: Partner directly with equity research analysts, quantitative researchers, and software engineers to identify AI use cases and integrate your solutions directly into their daily workflows. Requirements Education: Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related quantitative field. Experience: 3+ years of experience in Data Science or Machine Learning, with a demonstrable focus on NLP (Natural Language Processing) and Generative AI. Programming: High proficiency in Python and standard ML libraries (Pandas, NumPy, Scikit-learn). AI/LLM Tech Stack: Extensive experience with the modern GenAI stack, including Hugging Face, LangChain, LlamaIndex, Vector Databases (e.g., Pinecone, Milvus, Weaviate), and API integrations (OpenAI, Google Gemini, Anthropic). Deep Learning: Strong hands-on experience with frameworks like PyTorch or TensorFlow, specifically in training, evaluating, and fine-tuning transformer models. Problem Solving: A deep understanding of the limitations of LLMs (hallucinations, context window limits) and proven strategies to overcome them in production environmen
