AIM Fraud analytics team is seeking an experienced and innovative Data Scientist to join our Fraud Modeling / Gen AI team to transform fraud detection and prevention. As a subject matter expert in data science, you will be responsible for the development and deployment of cutting-edge data science solutions that enhance fraud detection and reduce false positives and optimize operational efficiency. Key Responsibilities: - Lead the design and implementation of generative AI use cases, from ideation to production. - Build and tune LLM-based applications using platforms like Vertex, GPT, Hugging Face, etc. - Create robust prompt engineering strategies and reusable prompt templates. - Integrate generative AI with enterprise applications using APIs, knowledge graphs, vector databases (e.g., PG Vector, Pinecone, FAISS, Chroma), and orchestration tools. - Collaborate with Tech and business teams to identify opportunities and build solutions. - Responsible for model development, validation and testing of fraud detection models, including statistical analysis, data validation and model performance evaluation. - Ensure compliance with regulatory requirements and industry best practices in fraud detection and model validation. - Responsible for documenting the model development documents for MRM approvals and governance purposes. - Stay current on GenAI trends, frameworks (LangChain, LlamaIndex), and research. - Mentor junior team members and promote a culture of experimentation and learning. - Stay abreast of advancements in Gen AI, LLMs, and fraud prevention technologies, applying relevant innovations to projects. - Specialization in fraud or risk domain preferred Qualifications: - 11 years of hands-on experience in data science, or AI/ML roles. - 7 years’ experience in statistical analysis with working knowledge of at least one of the following statistical software packages: Python (Must), Hive, Spark, SAS Strong quantitative, analytical, and problem-solving skills; knowledge of probability theory, statistics, mathematical finance, econometrics, numerical methods - 2 years of hands-on experience specifically with generative AI or LLMs. - Strong understanding of statistical concepts and modelling techniques including traditional and advanced ML algorithms - Strong programming skills in Python, and familiarity with libraries like Transformers, LangChain, LlamaIndex, PyTorch, or TensorFlow. - Working knowledge of retrieval-augmented generation (RAG) pipelines and vector databases. - Understanding of MLOps / LLM Ops, model evaluation, prompt tuning, and deployment pipelines - Experience building applications with OpenAI, Anthropic Claude, Google Gemini, or open-source LLMs. - Familiarity with regulatory requirements and guidelines related to risk model validation - Strong communication skills and the ability to partner with both technical and non-technical stakeholders. ------------------------------------------------------ **Job Family Group: ** Decision Management------------------------------------------------------ **Job Family:** Specialized Analytics (Data Science/Computational Statistics)------------------------------------------------------ **Time Type:** Full time------------------------------------------------------ **Most Relevant Skills ** Please see the requirements listed above.------------------------------------------------------ **Other Relevant Skills ** For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------ *Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.* * * *If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review **[Accessibility at Citi](https://www.citigroup.com/citi/accessibility/application-accessibility.htm).* *View Citi’s [EEO Policy Statement](https://www.citigroup.com/global/eeo-aa-policy) and the [Know Your Rights](https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) poster.*