Vice President - Data Science / Applied AI ML

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. Hands-on experience building Agentic AI solutions and AI orchestration workflows using frameworks such as LangGraph, LangChain, or equivalent platforms. Experience implementing Model Context Protocol (MCP) integrations and designing AI systems that securely connect to enterprise tools, data sources, APIs, and business workflows. Proficiency in designing, building, and querying Knowledge Graphs and graph databases such as Neo4j. Excellent problem-solving, communication, and collaboration skills. Familiarity with compliance, risk management, or regulatory processes within financial services is highly desirable.