Vice President - Data Science And Gen AI

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Job Overview

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.

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Job Family Group:

Decision Management

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Job Family:

Specialized Analytics (Data Science/Computational Statistics)

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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