Gen AI Scientist

Job Title: AI Scientist - Generative AI, RAG, Knowledge Graph & Agent-Based Modeling

Location: New York, NY

Company: Nelumbium Capital

About Nelumbium Capital

Nelumbium Capital is a forward-thinking quantitative hedge fund based in New York that integrates the latest advancements in AI, data science, and complex systems to drive innovative trading strategies. By applying cutting-edge methodologies to financial markets, we aim to generate superior returns while maintaining a robust, risk-adjusted approach. Our interdisciplinary team is composed of top-tier scientists, engineers, and traders focused on leveraging AI to uncover new opportunities and refine decision-making processes.

Job Overview

Nelumbium Capital is seeking an AI Scientist with expertise in Generative AI, Retrieval-Augmented Generation (RAG), Knowledge Graphs, and Generative Agent-Based Modeling to join our AI research team. In this role, you will help shape the future of quantitative finance by applying advanced AI techniques to model and predict market dynamics, develop innovative trading algorithms, and build intelligent systems that enhance decision-making processes.

You will work on solving complex problems in areas such as financial forecasting, market behavior modeling, and the creation of next-gen AI-driven trading strategies. Your research will leverage cutting-edge AI frameworks, integrating diverse data sources into knowledge graphs, developing agent-based models, and utilizing generative AI to simulate, predict, and optimize financial market strategies.

Key Responsibilities

• Research and develop state-of-the-art Generative AI models for data synthesis, scenario generation, and market behavior prediction.
• Design and implement Retrieval-Augmented Generation (RAG) systems that leverage large-scale datasets and real-time financial information to improve model accuracy and adaptability.
• Develop Knowledge Graphs to represent and extract insights from vast, unstructured financial data, linking disparate information for better decision-making and enhanced predictive power.
• Build and refine Generative Agent-Based Models (ABM) to simulate complex market environments and agent interactions that inform risk management and trading strategies.
• Collaborate closely with quantitative researchers, data scientists, and portfolio managers to integrate AI-driven insights into portfolio construction and risk management frameworks.
• Continuously test and validate AI-driven models against real-world data to improve performance, scalability, and robustness.
• Stay up-to-date with the latest advancements in AI and machine learning techniques, contributing to the development of novel methods that push the envelope in financial modeling and trading.

Required Qualifications

• PhD or equivalent experience in Computer Science, Artificial Intelligence, Applied Mathematics, or a related field, with a focus on Generative AI, Knowledge Graphs, or Agent-Based Modeling.
• Strong understanding of Generative AI techniques, including GANs, VAEs, and other deep generative models.
• Experience with Retrieval-Augmented Generation (RAG) approaches and integrating knowledge bases with generative models.
• Expertise in designing and deploying Knowledge Graphs for real-time data processing and insight generation.
• Solid understanding and hands-on experience with Agent-Based Modeling (ABM) and its application to complex, multi-agent environments such as financial markets.
• Proficiency in programming languages such as Python, TensorFlow, PyTorch, or similar.
• Experience with modern machine learning frameworks, large-scale data processing, and cloud technologies.
• Strong analytical mindset with a deep understanding of financial markets, asset pricing, and market microstructure is a plus.
• Excellent communication skills to effectively collaborate with cross-functional teams and present complex concepts to non-technical stakeholders.

Preferred Qualifications

• Previous experience in a quantitative hedge fund or a financial technology company, working with large-scale financial datasets and trading algorithms.
• Experience with reinforcement learning and its applications in decision-making and financial modeling.
• Published research in top-tier AI or machine learning journals and conferences.
• Familiarity with data mining, graph theory, and natural language processing (NLP) in the context of financial markets.

Why Join Nelumbium Capital?

• Join a team at the forefront of AI and quantitative finance innovation.
• Work in a highly collaborative, intellectually stimulating environment with cutting-edge tools and resources.
• Competitive salary, performance-based bonuses, and equity participation.
• Opportunities for continuous learning, professional growth, and cross-disciplinary collaboration.
• Be part of a diverse and dynamic company culture that values creativity, initiative, and a passion for solving complex problems.

If you are passionate about applying Generative AI, Knowledge Graphs, and Agent-Based Modeling to real-world financial challenges and are eager to shape the future of quantitative finance, Nelumbium Capital offers an exciting opportunity to make a significant impact.

How to Apply

Please submit your resume, along with a cover letter highlighting your relevant expertise and explaining your interest in working at Nelumbium Capital.