Asset Management - AI Quant Analyst - Artificial Intelligence & Machine Learning Focus

JPMorgan Chase JPMorgan Chase · Banking · Shanghai, China · Asset & Wealth Management

JPMorgan Chase is seeking an AI Quant Analyst with a focus on AI/ML for their Asset Management division in Shanghai. The role involves researching and implementing quantitative investment models using ML/DL, applying LLMs/NLP to financial data for insights, and collaborating with teams to deploy models. The position requires a Master's or PhD in a quantitative field, 3+ years of experience in quantitative research within finance, and proven expertise in ML/DL/AI, particularly LLMs/NLP for financial data. Strong coding skills in Python and experience with statistical modeling are essential. The role also requires knowledge of financial markets and regulatory compliance.

What you'd actually do

  1. Research and implement quantitative investment models using machine learning and deep learning techniques across equities, fixed income, commodities, and other asset classes.
  2. Apply advanced AI methods, including large language models and natural language processing (NLP), to extract insights from textual data for sentiment analysis, event detection, and alternative data integration.
  3. Conduct rigorous research to identify new alpha signals, improve existing strategies, and enhance predictive accuracy in investment decision-making.
  4. Collaborate with portfolio managers, research analysts, and engineers to implement models in production, optimize portfolios, and manage risk exposures.
  5. Stay current of the latest advancements in AI/ML/LLMs and their applications in investment research and management, contributing to the firm's innovation in investment strategies and capabilities.

Skills

Required

  • Master’s or PhD degree in a quantitative discipline
  • 3+ years of experience in quantitative research or analysis within asset management, hedge funds, investment banking, or a similar financial environment.
  • Proven expertise in machine learning, deep learning, and AI techniques
  • Hands-on experience applying LLMs/NLP to financial or textual data.
  • Strong coding and data analysis skills
  • Python experience
  • Experience with statistical modeling, time-series analysis, back-testing frameworks, and big data tools.
  • Knowledge of financial markets, asset pricing, portfolio theory, and risk management.
  • Excellent problem-solving abilities
  • Strong and effective communication skills

Nice to have

  • Experience with generative AI, diffusion models, or agentic workflows in finance.
  • Familiarity with alternative data sources and their integration into investment processes and strategies.
  • Track record of developing profitable trading signals or models using ML/LLM techniques.
  • R or MATLAB experience
  • SQL experience
  • SPARK experience
  • Familiarity with large financial databases
  • CFA or equivalent

What the JD emphasized

  • Attainment of all necessary regulatory licenses (or any other licenses / qualifications as required) for carrying out Asset Management and other regulated activities

Other signals

  • Apply advanced AI methods, including large language models and natural language processing (NLP), to extract insights from textual data for sentiment analysis, event detection, and alternative data integration.
  • Conduct rigorous research to identify new alpha signals, improve existing strategies, and enhance predictive accuracy in investment decision-making.
  • Stay current of the latest advancements in AI/ML/LLMs and their applications in investment research and management, contributing to the firm's innovation in investment strategies and capabilities.