JPMorgan Chase

AI Research Scientist role at JPMorgan Chase focused on developing novel techniques, tools, and frameworks for large-scale problems in financial services. The role involves formulating problems, developing algorithms and models, conducting experiments, and contributing to business applications, open-source software, and patents.

AI Research Scientist role at JPMorgan Chase focused on developing novel techniques, tools, and frameworks for large-scale problems in financial services. The role involves formulating problems, developing algorithms and models, conducting experiments, and contributing to business applications, open-source software, and patents.

Machine Learning Scientist - NLP - VP role focused on developing and deploying Generative AI solutions within JPMorgan Chase's Machine Learning Center of Excellence. The role involves research, thought partnership, cross-functional collaboration, and leading firm-wide initiatives to apply ML models across the business. Requires a PhD or MS with experience in GenAI, ML/DL toolkits, experimental design, and communication skills.

Machine Learning Scientist specializing in NLP and Generative AI (GenAI) to develop and deploy state-of-the-art models for complex business challenges within JPMorgan Chase. The role involves research, thought partnership with leaders, cross-functional collaboration for production deployment, and leading firm-wide initiatives with large-scale frameworks. Requires a PhD or MS with experience in GenAI, ML/DL toolkits, experiment design, and communication skills.

Machine Learning Scientist (VP) in the Machine Learning Center of Excellence at JPMorgan Chase, focusing on NLP and Generative AI. The role involves owning the full lifecycle of ML solutions, from research and development to production deployment, acting as a thought leader, and driving cross-functional collaboration to implement new ML methods and large-scale frameworks for business impact within the financial services industry.

Quantitative Analyst with a focus on AI/ML/LLMs for investment research, alpha generation, portfolio optimization, and risk management in financial markets. Responsibilities include researching and implementing quantitative models, applying NLP to textual data, identifying alpha signals, and collaborating with teams to implement models in production. Requires a quantitative Master's/PhD, 3+ years of experience, expertise in ML/DL/AI/LLMs/NLP, strong coding skills (Python), and knowledge of financial markets. Regulatory licenses are required.

AI Researcher Senior Associate at JPMorgan Chase, focused on developing novel AI/ML techniques and models for complex, large-scale problems within the financial services domain. The role involves research projects, formulating problems, developing algorithms, conducting experiments, and contributing to business applications, open-source software, and patents.

JPMorgan Chase is seeking an Applied AI ML Researcher Senior Associate to build next-generation autonomous agents for the financial industry. This role focuses on developing GenAI and Agentic solutions to automate complex operational processes, deliver collaborative agents that orchestrate workflows, and contribute to the production deployment of AI/ML solutions.

Research Scientist role focused on applying sophisticated machine learning methods, particularly NLP and LLMs, to real-world problems within a financial services context. The role involves developing state-of-the-art models, publishing research, and collaborating to deploy solutions into production. It emphasizes both research exploration and practical application, with a focus on post-training and potentially agentic systems.

This role focuses on applying advanced ML methods like time series analysis, reinforcement learning, causal inference, and NLP to solve real-world problems in finance. The associate will research new methods, develop state-of-the-art models, collaborate with various teams to deploy solutions, and drive firm-wide initiatives. A PhD in a quantitative discipline and hands-on experience with ML toolkits are required, with a preference for candidates with financial industry knowledge and published research.

Quantitative Equity Researcher (VP) at JPMorgan Chase focused on developing novel alpha signals and enhancing return-forecasting models using advanced statistical, econometric, and machine learning techniques, including LLMs and generative AI. The role involves applying these techniques to large datasets, designing research pipelines, building research frameworks, and collaborating with portfolio managers and technology teams to integrate research into production systems. Requires strong Python and SQL skills, and experience with NLP and alternative data for repeatable research.

PhD-level Quant Researcher with 0-3 years of experience in machine learning, specializing in reinforcement learning, to develop alpha signals and portfolio construction methodologies for global equity markets. Responsibilities include data analysis, model enhancement, and integrating research into production systems.

Quantitative trading firm seeks a VP to research, develop, and deploy mid-frequency systematic trading strategies. Role involves applying statistical modeling and machine learning to financial markets, with a focus on alpha generation, portfolio construction, risk management, and execution. Requires end-to-end ownership from ideation to live trading and performance monitoring.

Seeking a VP to join Credit Quantitative Trading team, leveraging AI/ML to enhance trading strategies and decision-making. The role involves exploring and integrating AI/ML methodologies, developing and deploying models end-to-end in production, and ensuring robustness and scalability. Requires experience in quantitative research, fixed income markets, and AI/ML timeseries models.

Quantitative researcher for an Equity Derivatives team, focusing on end-to-end alpha research and strategy deployment. Responsibilities include feature engineering, building calibration/attribution/monitoring frameworks, and implementing systematic strategies using data analytics, statistical modeling, and machine learning. The role also involves leveraging AI/ML tooling to accelerate research and improve productivity.

Quantitative Equity Researcher (VP) at JPMorgan Asset Management, focusing on developing novel alpha signals and enhancing return forecasting models using advanced statistical, econometric, and machine learning techniques on large datasets. The role involves research in portfolio construction and risk management, translating insights into investment strategies, and collaborating with technology teams for model integration.

This role focuses on quantitative research within Wealth Management, developing and maintaining models for asset allocation, portfolio construction, risk management, and performance attribution. It involves applying statistical and machine learning techniques to large datasets and collaborating with portfolio managers and other stakeholders. The role requires strong Python programming skills and a background in quantitative fields.