Data Scientist GenAI (Banking Domain)

As a Data Scientist specializing in GenAI within the Banking domain, you will utilize your extensive experience of over 10 years in Data Science, with a focus of 3+ years specifically in GenAI. Your expertise will be instrumental in developing, training, and fine-tuning GenAI models such as LLMs and GPT for various banking use cases. You will collaborate closely with business and product teams to design and implement predictive models, NLP solutions, and recommendation systems tailored to the financial industry. A key aspect of your role will involve working with large volumes of both structured and unstructured financial data to derive valuable insights. Moreover, you will be responsible for ensuring the ethical and compliant use of AI by incorporating practices related to fairness, explainability, and compliance into the model outputs. Deployment of these models using MLOps practices like CI/CD pipelines and model monitoring will also be within your purview. Your skill set must include a strong proficiency in Python programming, along with a deep understanding of libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch. Hands-on experience with GenAI tools like OpenAI, Hugging Face, LangChain, and Azure OpenAI will be crucial for success in this role. Furthermore, your expertise in NLP, prompt engineering, embeddings, and vector databases will play a pivotal role in building models for critical banking functions like credit risk assessment, fraud detection, and customer segmentation. While not mandatory, it would be advantageous to possess knowledge of LLM fine-tuning and retrieval-augmented generation (RAG) in addition to familiarity with data privacy and compliance regulations such as GDPR and RBI guidelines as they pertain to AI systems. Your understanding of banking data, processes, and regulatory requirements will be key in delivering effective AI-driven solutions within the financial services industry.,