Data Scientist Vice President

Overview

Design, develop and deploy enterprise-grade AI solutions that help Third-Party Management teams assess, monitor and manage supplier and vendor risks, combining software engineering, AI engineering, analytics and product development.

What you'll do

• Design and build enterprise AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and agentic AI architectures.
• Develop AI-powered copilots, knowledge assistants, workflow automation and decision-support tools.
• Build reusable AI services, APIs and components for enterprise adoption.
• Develop multi-agent workflows for complex business processes.
• Design enterprise knowledge repositories using vector databases and knowledge graphs.
• Build document ingestion, metadata extraction, semantic search and retrieval pipelines.
• Improve retrieval quality through evaluation and continuous optimization.
• Ensure knowledge assets remain governed, traceable and reusable.
• Build scalable Python-based backend services and APIs.
• Develop modern web applications using enterprise UI frameworks.
• Integrate AI services with internal data platforms and enterprise applications.
• Write clean, modular and production-ready code.
• Ensure AI solutions comply with enterprise governance, security and model risk requirements.
• Support model evaluation, monitoring, auditability and explainability.
• Collaborate with AI governance teams on documentation and deployment approvals.
• Partner with business stakeholders to understand challenges and identify AI opportunities.
• Work closely with technology, architecture, cybersecurity and data engineering teams.
• Support production deployment and operationalization of AI solutions.
• Mentor junior engineers and contribute to AI engineering best practices.

What you'll need

• Bachelor's degree in computer science, engineering, mathematics or a related discipline.
• Significant experience in software engineering, AI engineering, analytics or data science.
• Strong Python programming skills.
• Experience building REST APIs and backend applications.
• Knowledge of SQL and data engineering concepts.
• Experience working with cloud platforms and enterprise application development.
• Strong problem-solving and stakeholder management skills.
• Excellent written and verbal communication.

Nice to have

• Master's degree.
• Experience in one or more of: LLM application development, Retrieval-Augmented Generation (RAG), agentic AI frameworks, prompt engineering, vector databases, knowledge graphs, AI orchestration frameworks, enterprise AI platforms, model evaluation frameworks, MLOps or LLMOps, Kubernetes, CI/CD, banking, financial services or risk management.

Details

• Full-time role.
• Office setting with minimal travel required.
• Minimal physical effort required.