Data Science Analyst

• Work with large and complex datasets using a variety of tools (Python, PySpark, SQL, Hive, etc.) and frameworks to build Deep learning/generative AI solutions for various business requirements
• Primary focus areas include model training/fine-tuning, model validation, model deployment, and model governance related to multiple portfolios
• Design, fine-tune and implement LLMs/GenAI applications using techniques like prompt engineering, Retrieval Augmented Generation (RAG) and model fine-tuning
• Responsible for documenting data requirements, data collection/processing/cleaning, and exploratory data analysis, including utilizing deep learning /generative AI algorithms and, data visualization techniques
• Collaborate with team members and business partners to build model-driven solutions using cutting-edge Generative AI models (e.g., Large Language Models) and also at times, ML/traditional methods (XGBoost, Linear, Logistic, Segmentation, etc.)
• Work with model governance & fair lending teams to ensure compliance of models in accordance with Citi standards
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules, and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency

• Bachelor’s Degree with at least 3 years of experience in data analytics
• Master’s Degree with 2 years of experience in data analytics
• PhD
• Hands-on experience in PySpark/Python/R programing along with strong experience in SQL
• 2-4 years of experience working on deep learning, and generative AI applications
• Experience working on Transformers/ LLMs (OpenAI, Claude, Gemini etc.,), Prompt engineering, RAG based architectures and relevant tools/frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, LangChain, LlamaIndex etc.,
• Solid understanding of deep learning, transformers/language models
• Familiarity with vector databases and fine-tuning techniques
• Experience working with large and multiple datasets, data warehouses and ability to pull data using relevant programs and coding
• Strong background in Statistical Analysis
• Capability to validate/maintain deployed models in production
• Self-motivated and able to implement innovative solutions at fast pace
• Strong communication skills
• Multiple stake holder management
• Strong analytical and problem solving skills
• Excellent written and oral communication skills
• Strong team player
• Control orientated and Risk awareness
• Working experience in a quantitative field
• Willing to learn and can-do attitude
• Ability to build partnerships with cross-function leaders

Experience in Credit Cards and Retail Banking is preferred