VP - Data Science & Gen AI

VP - Data Science & Gen AI

Apply (opens in new window)

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.

• 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 (Lang Chain, Llama Index), 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.

• 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, Lang Chain, Llama Index, PyTorch, or Tensor Flow.
• 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

Location: Bengaluru, Karnataka, India;
Pune, Maharashtra, India

Job Type: Hybrid

Posted: Mar. 10, 2026

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to 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 w Citi’s EEO Policy Statement and the Know Your Rights poster.