Data Scientist

GenAI Development: Design, develop, and fine-tune Large Language Models (LLMs) and implement RAG (Retrieval-Augmented Generation) frameworks to enhance platform intelligence. Python Engineering: Write clean, scalable, and efficient Python code for data processing, model training, and API integration. Technical Governance: Adhere to strict Compliance Gates and security protocols to ensure all AI deployments meet enterprise safety standards. Process Optimization: Utilize and optimize IDE plugins and developer tools to enhance the overall DevX (Developer Experience) and speed to market. Strategic Impact: Collaborate with the Account Management team to identify strategic investment opportunities in AI that can drive cost-efficiency and performance gains.

Required Technical Skills

Core AI: Deep understanding of Transformers, LLMs (GPT, Llama, Claude), and Prompt Engineering. Programming: Mastery of Python and its ecosystem (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Frameworks: Experience with LangChain, LlamaIndex, or Vector Databases (Pinecone, Weaviate, Milvus). Cloud & MLOps: Familiarity with deploying models on Azure or AWS, and managing the end-to-end model lifecycle. <\/span><\/span><\/span>

<\/span>