Data Scientist - GenAI (Banking Domain)

As a Data Scientist specializing in GenAI within the Banking domain, you will leverage your extensive experience of over 10 years in Data Science, with a specific focus of 3+ years in GenAI. Your key responsibility will revolve around developing, training, and fine-tuning GenAI models such as LLMs, GPT, etc., tailored for banking use cases. Additionally, you will be tasked with designing and implementing predictive models, NLP solutions, and recommendation systems while working with large volumes of structured and unstructured financial data. Collaboration with business and product teams to define AI-driven solutions will be crucial in your role. You will play a pivotal part in ensuring responsible AI practices, fairness, explainability, and compliance in model outputs. Deployment of models using MLOps practices including CI/CD pipelines and model monitoring will also be within your purview. Your skill set must include strong proficiency in Python programming along with libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch. Hands-on experience with GenAI tools such as OpenAI, Hugging Face, LangChain, Azure OpenAI, etc., will be essential. Expertise in NLP, prompt engineering, embeddings, and vector databases is a prerequisite. Furthermore, you should have experience in building models for credit risk assessment, fraud detection, customer segmentation, among others. A solid understanding of banking data, processes, and regulatory requirements is essential for success in this role. Moreover, having knowledge in LLM fine-tuning and retrieval-augmented generation (RAG) is considered a good-to-have skill. Exposure to data privacy and compliance standards such as GDPR, RBI guidelines, in AI systems will be an added advantage.,