Vice President, Modelling Data Scientist - AI Labs

Collaborate with scientists, engineers, and investment professionals to develop methodologies for client, investor, and operational problems Own the entire solution lifecycle from scoping, research, and prototyping through scaled implementation, productionalization, and internal review Deliver major projects and key initiatives for AI Labs Translate business needs into well-scoped AI/ML solutions with stakeholders Design, build, and evaluate AI agents and agentic workflows involving tool use, memory, and multi-step reasoning on large datasets Rapidly prototype agentic solutions using AI/ML tools, agent frameworks, orchestration platforms, and foundation model APIs Build production-grade, reliable, scalable solutions with engineers and stakeholders while meeting firm-wide compliance processes Implement agent observability, guardrails, and evaluation pipelines Define and maintain evaluation frameworks measuring agent quality, safety, and reliability in production Present technical work to senior leaders and general audiences Promote thought leadership through white papers, publications, and presentations Requirements PhD in a quantitative field with 4+ years of professional experience OR MS degree in a quantitative field plus 7+ years of professional experience in machine learning, artificial intelligence, or other aspects of the AI/data science and agent development process Strong familiarity with Python programming Strong theoretical background in and practical experience using AI, machine learning, optimization, or statistical techniques Experience assessing performance of machine learning methods and agentic systems, including benchmark construction, metric design, and statistically sound measurement of quality, safety, and reliability Ability to work within a team environment and collaborate and communicate across cross-functional groups Depth in one or more relevant research areas, such as LLM reasoning, reinforcement learning, machine learning, statistical modeling, or quantitative optimization Experience building and deploying AI agents and agentic workflows using open-source frameworks, agent platforms, or comparable tools Experience with standards such as Model Context Protocol (MCP) Experience with retrieval-augmented generation, embedding models, vector databases, and long-term memory Experience with machine learning libraries such as PyTorch Experience with cloud platforms such as AWS, Azure, or GCP Experience with analysis of financial or economic data Experience building production-grade solutions and leading technical projects or managing Core Competencies Demonstrates expertise in developing and implementing AI/ML solutions, with a strong focus on agentic workflows and performance evaluation. Proficient in collaborating with cross-functional teams to deliver scalable, production-grade solutions while adhering to compliance standards. Highest-signal resume keywords PhD In Quantitative Field Python Programming Machine Learning Experience AI Agent Development Cloud Platforms Experience ATS Optimization Keywords Hard Skills AI Machine Learning Statistical Techniques Optimization Benchmark Construction Metric Design Retrieval-Augmented Generation Embedding Models Vector Databases Long-Term Memory Soft Skills Collaboration Communication Teamwork Industry Keywords Model Context Protocol Financial Data Analysis Economic Data Analysis Tools & Technologies PyTorch AWS Azure GCP Open-Source Frameworks Agent Platforms #J-18808-Ljbffr Jobtailor