Vice President - Data Science And Gen AI

Citibank (Switzerland) AG; Pune District; On-site; Confidential; Full time

Job summary

Citibank (Switzerland) AG seeks an experienced Vice President to lead the Fraud GenAI team. You will build and guide a high-performing data science group, drive GenAI solutions, and collaborate with Technology, Risk, and Compliance to transform fraud operations with advanced AI.

You will mentor teams, oversee project delivery from ideation to production, and ensure regulatory compliance in model risk management. Strong communication and stakeholder management are essential for success.

Qualifications

• 9+ years of hands-on data science or AI/ML experience.
• 3+ years in people leadership or team lead roles.
• Strong Python and ML library skills (Transformers, LangChain, PyTorch, TensorFlow).

Responsibilities

• Lead and develop a high-performing Fraud Analytics GenAI team.
• Navigate end-to-end design and production of GenAI use cases and LLM applications.
• Ensure model development, validation, and regulatory compliance in risk domains.
• Engage senior stakeholders and communicate complex concepts effectively.

Skills

Leadership

Python

Transformers

LangChain

LlamaIndex

PyTorch

TensorFlow

MLOps

RAG

Vector databases

Communication

Education

Bachelor's/Master's in Statistics/Technology/Economics

Tools

Vertex AI

Hugging Face

Pinecone

FAISS

Chroma

PG Vector

Job description

The AIM Fraud Operations Analytics team is seeking an experienced, innovative, and people-oriented Vice President to lead our Fraud GenAI team. As a senior leader and subject matter expert in data science and generative AI, you will be responsible for building and leading a high-performing team of data scientists while driving the design, development, and deployment of cutting‑edge data science and GenAI‑based solutions. This role focuses on transforming fraud operations processes through advanced AI while fostering team growth, cross‑functional collaboration, and operational excellence.

Responsibilities

• Leadership & People Management Lead, mentor, and develop a team of data scientists, fostering a culture of innovation, experimentation, and continuous learning. Provide technical and career guidance, conduct performance reviews, and support talent development and succession planning. Build and scale a high‑performing Fraud Analytics GenAI team, including hiring, onboarding, and performance management.
• Project & Delivery Leadership Lead the end-to-end design and implementation of generative AI use cases, from ideation to production. Oversee the building and tuning of LLM‑based applications using platforms such as Vertex, GPT, Hugging Face, etc. Drive robust prompt engineering strategies and the creation of 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 Technology, Business, and other stakeholders to identify opportunities, prioritize initiatives, and deliver high‑impact solutions. Manage end‑to‑end project delivery, ensuring on‑time, high‑quality outcomes within regulatory and risk frameworks.
• Technical & Domain Expertise 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, MRM (Model Risk Management) standards, and industry best practices in fraud detection and GenAI. Document model development artifacts for MRM approvals and governance purposes Stay current with GenAI trends, research, and advancements in fraud prevention. Apply relevant innovations to fraud and risk domain projects (specialization in fraud or risk domain preferred).
• Stakeholder Management Partner effectively with senior business leaders, technology teams, risk, compliance, and other stakeholders. Present complex technical concepts and project updates to both technical and non‑technical audiences. Influence decision‑making and secure buy‑in for GenAI and data science initiatives across the organization.

Qualifications

• 9+ years of hands‑on experience in data science or AI/ML roles, with at least 3+ years in a people leadership or team lead capacity. Proven track record of designing and developing data science / GenAI‑based solutions in production environments. Strong programming skills in Python and familiarity with libraries such as 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. Familiarity with regulatory requirements and guidelines related to risk and model validation. Strong leadership, project management, and stakeholder management skills with the ability to influence and partner with both technical and non‑technical stakeholders. Excellent communication and presentation skills.

Education

Bachelors/University degree, Master’s degree in Statistics / Technology / Economics preferred

This job description provides a high‑level review of the types of work performed. Other job‑related duties may be assigned as required.

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. View Citi’s EEO Policy Statement and the Know Your Rights poster.