JOB DESCRIPTION
Job summary:
As a Vice President – Data Science/Applied AI ML, you will design, build, and deploy next-generation AI solutions for complex compliance and risk management challenges. The ideal candidate combines deep technical expertise in LLMs, GenAI, AI orchestration frameworks, Agentic AI, and analytics with a passion for solving business problems.
This role will partner closely with Compliance, Technology, Data, and Product teams to rapidly prototype ideas, develop production-ready solutions, and drive the adoption of AI capabilities across the organization.
Job
Responsibilities
- Design, develop, and deploy AI-powered solutions leveraging LLMs, Generative AI, Agentic AI, and advanced analytics.
- Build proof-of-concepts and rapidly prototype new AI capabilities to validate business value and technical feasibility.
- Develop AI agent workflows and orchestration frameworks that integrate models, tools, APIs, and enterprise data sources.
- Design and implement MCP-based (Model Context Protocol) integrations to enable secure, scalable access to enterprise data, tools, and business processes.
- Design and implement Retrieval-Augmented Generation (RAG), GraphRAG, and Knowledge Graph solutions to improve the accuracy and explainability of AI outputs.
- Integrate enterprise LLM platforms and GenAI services into analytical and operational workflows.
- Perform data exploration, experimentation, model evaluation, and performance optimization across structured and unstructured datasets.
- Develop scalable Python-based applications, services, and APIs supporting AI and analytics use cases.
- Create user-interfaces, analytical applications, and self-service solutions that transform AI outputs into actionable insights.
- Collaborate with Compliance, Technology, and Business stakeholders to understand
requirements
and deliver impactful solutions.
- Contribute to engineering standards, AI best practices, governance frameworks, and technical mentoring across the team.
Required Qualifications
and Skills:
- Master's degree or PhD in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, Economics, or a related quantitative discipline from a top-tier university.
- 10+ years of experience in AI/ML, Advanced Analytics, or Data Science, with significant recent experience in LLMs, Generative AI, and NLP.
- Strong hands-on programming expertise in Python and SQL, including development of production-quality applications and data pipelines.
- Deep understanding of LLM architectures, transformers, prompt engineering, model evaluation, and responsible AI practices.
- Experience developing solutions using frameworks such as PyTorch, TensorFlow, Hugging Face, or equivalent AI ecosystems.