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.

This role focuses on designing and running large-scale quantitative research to generate actionable customer insights that shape data-driven user experiences across digital products and services, with a focus on AI-driven/agentic customer experience transformation. The role requires proficiency in quantitative research methods, statistical analysis, and experience with statistical software. While the role touches on AI, its core function is in quantitative research and insight generation for customer experience, not direct AI/ML model development.

Senior quantitative portfolio manager for an equity team, responsible for setting the quantitative research agenda, owning core portfolio analytics and risk frameworks, and driving implementation of systematic, factor-based, and data-driven insights for an $80bn equity portfolio. The role involves translating complex quantitative work into investment decisions, leading the integration of quantitative signals with fundamental views, owning risk model applications, designing portfolio construction frameworks, driving development of research and analytics tooling (Python-first), and evaluating/applying machine learning/AI techniques for feature engineering, ensemble methods, and NLP for alternative data, with an emphasis on interpretability and investment relevance.

The role involves quantitative research for portfolio analytics within Wealth Management. Responsibilities include developing and running risk and performance attribution models for multi-asset portfolios, building and maintaining models using Python and MATLAB, and applying statistical and machine learning techniques to investment research. The role also involves data management, model documentation, testing, and validation, as well as collaboration with portfolio managers and technology teams.

Quantitative researcher for an equity derivatives flow desk, focusing on advanced analytics, optimization, and modeling for volatility trading. Responsibilities include developing pricing and risk models, client analytics, and hedging optimization tools, leveraging machine learning and data-driven techniques.

Quantitative researcher for equity eTrading at JPMorgan Chase, focusing on developing and improving algorithmic execution strategies using advanced quantitative models and statistical analysis. The role involves analyzing large datasets, back-testing methodologies, and collaborating with various teams to deliver innovative trading solutions.

JPMorgan Chase is seeking a Quantitative Investment Analyst to join their Equity Portfolio Management team. The role involves combining fundamental equity analysis with quantitative and factor-based approaches, supporting risk modeling, portfolio construction, and quantitative research using Python/R. The candidate will also contribute to the application of AI/ML techniques to enhance investment research and portfolio management.

The role involves quantitative trading research, optimizing a systematic trading platform using statistical models and machine learning, and providing execution consultancy. Responsibilities include designing research projects, analyzing market data for signals, enhancing trading performance, developing optimal execution strategies, and creating trade analytics frameworks with dashboards and tools for TCA, market impact, and slippage. The candidate will lead cross-functional projects and collaborate with traders, portfolio managers, and technology teams. Requires advanced Python, financial database expertise, trading knowledge (market-making, statistical arbitrage, systematic trading), technical communication skills, market microstructure knowledge, Git experience, and applied ML experience (RL, NLP, deep learning).

Research Analyst role at JPMorgan Chase focused on equity research, requiring financial modeling, valuation, and industry analysis. The role involves applying data analytics, automation, and AI/LLM tools to enhance analysis and workflows, alongside traditional research tasks. Requires a minimum of 1 year of experience in a relevant analytical role and a degree in a quantitative or financial field, with a core capability in statistics, programming, and AI/LLM use.

Quantitative researcher for a credit trading team, focusing on designing and implementing signals for corporate bonds and indices, analyzing P&L drivers, market trends, and large datasets. The role involves using statistical modeling and potentially AI/ML techniques to inform algorithmic trading strategies and optimize competitiveness in systematic credit trading.

This role supports a Security & Resiliency Initiative (SRI) by preparing pitch books, conducting research, financial valuations, and applying AI/LLM tools to enhance deliverables. It focuses on identifying risks in strategic supply chains and deploying financing solutions, often in partnership with the public sector, to enhance economic security and operational resilience in critical industries.

This role focuses on user research within a financial enterprise, with a secondary emphasis on exploring and evaluating AI tools for research operations. The primary function is to support and conduct user research, analyze data, and inform user experience design decisions. While AI tools are mentioned, the core of the role is traditional UX research, not AI model development or deployment.

This is a fellowship program for PhD students to gain industry experience in the Global Commodities Group at JPMorgan Chase, focusing on applying quantitative and computational expertise to real-world business problems in commodities and financial markets within the Systematic Trading business. It emphasizes professional skill development and applied problem-solving over academic research.

This role focuses on developing and distributing macroeconomic scenarios for financial forecasting within JPMorgan Chase's Office of the Chief Financial Officer. It involves collaborating with various teams, covering key economic indicators, and executing forecasts. The role requires strong quantitative skills, experience in research/forecasting, and proficiency in data synthesis and communication. Experience with AI/ML is a plus but not core to the role.

This role is for a Vice President in Global Research focusing on Latam Corporate Credit. The primary responsibilities include analyzing financials, forming credit views, building financial models, and producing research reports for institutional investors. The role requires a deep understanding of corporate credit fundamentals, experience with high yield credits and complex capital structures, and advanced Excel modeling skills. Familiarity with AI-enabled tools is mentioned as a requirement to enhance analytical output.

Economic Research Analyst role supporting global economics research platform, analyzing macroeconomic and financial market trends in frontier and emerging markets. Requires advanced quantitative and econometric techniques, large dataset management, and contribution to research publications.

Research Scientist role focused on quantum computing within financial technology, involving foundational theory, simulation, hardware experimentation, and financial applications. Requires a Ph.D. and strong publication record in quantum computing or related fields.

Research Scientist role focused on quantum computing for financial technology, involving algorithm development, hardware experimentation, and business application identification. Requires a Ph.D. and a strong publication record in quantum computing or related fields.

This role focuses on analyzing macroeconomic and financial data to understand consumer and business health, identify trends, and communicate insights. It involves data design, modeling, analysis, and visualization, with a basic understanding of statistics, econometrics, and machine learning. The primary output is insights and explanations, not AI models or products.

Quantitative trading role focused on designing and implementing algorithmic trading solutions for macro asset classes, involving strategy formulation, back-testing, and low-latency infrastructure development.

Quantitative Research Associate in Wholesale Credit Risk group, focusing on counterparty credit risk models and metrics. Responsibilities include enhancing frameworks, developing statistical models, designing software in Python, and partnering with control and tech teams. Requires experience in quantitative research/risk modeling, a strong quantitative educational background, and programming skills in Python & R. Familiarity with financial instruments and risk management methodologies is preferred.

This role supports US Investment Grade (IG) credit strategy by monitoring markets, maintaining data infrastructure, analyzing macro developments, and contributing to publications. It involves data-driven research, modeling, and communication of insights.

This role is within JPMorgan Chase's Central Research Group (CRG), supporting the Banking & Markets operation. The Technical Transaction Analyst will focus on the oil and gas sector, performing technical evaluations of assets, analyzing data, creating decline curves, and building corporate models to assist in client advisory roles. The role involves data analysis, programming (Python, VBA, R), and collaboration with banking and investment teams.

This role focuses on user experience research within Cybersecurity Technology and Controls at JPMorgan Chase, aiming to shape product design by uncovering customer needs and behaviors. It involves designing and executing research studies, analyzing data using advanced methods, and mentoring junior researchers. While it mentions AI tooling as a preferred skill, the core function is user experience research, not AI model development.

Quantitative trading and research role focused on designing and implementing systematic trading strategies for FX, Rates, Commodities, and Credit markets, with an emphasis on market microstructure and high-frequency trading. Responsibilities include analyzing market data, generating signals, and collaborating with technology partners.

Research Scientist role focused on quantum error correction and fault-tolerant quantum computation, involving development, numerical investigation, and experimental validation of protocols for quantum computing hardware. The role requires a Ph.D. and experience with quantum computing software frameworks and programming languages, with a strong publication record.

Research Scientist role focused on quantum error correction and fault-tolerant quantum computation, involving development, numerical investigation, and experimental validation of protocols for quantum computing hardware. The role requires a Ph.D. and experience with quantum computing software frameworks and programming languages, with a strong publication record.

Quantitative Trader Associate role focused on the US Interest Rate Swap market, involving research on trading strategies, data analysis, back testing, and expanding modeling tools. Requires strong programming skills and knowledge of quantitative fields.

Quantitative Research Analyst role focused on designing, analyzing, and delivering quantitative models for Wholesale Credit Stress (CCAR, ICAAP, Risk Appetite) and loan loss reserves. Utilizes statistical techniques and programming languages like Python or R for building forecasting models.

Lead client coverage on regional rates markets, formulate views on Asian bond markets, issue trade recommendations, and deliver the firm’s Asia Local Markets bond outlook. Requires significant experience publishing on Emerging Markets fixed income strategy and interfacing with clients at a senior level.

Quantitative Strategist role focused on cross-asset risk premia research, developing systematic strategies, and contributing to research publications within JPMorgan Chase's Global Research team. Requires a Master's or Ph.D. in a quantitative subject, strong Python coding skills, and knowledge of machine learning and big data.