Quantitative Research, Associate

JPMorgan Chase JPMorgan Chase · Banking · Singapore · Commercial & Investment Bank

Quantitative Research Associate at JPMorgan Chase in Singapore, focusing on developing and maintaining mathematical models for financial transactions, algorithmic trading, and risk management. The role involves partnering with business leaders, trading desks, and technology teams to create analytical tools and quantitative models, ensuring compliance with regulatory requirements, and contributing to financial engineering innovation. Requires a Ph.D or Master's in a quantitative field, 2 years of experience, strong programming skills (C++/Java, Python), and knowledge of AI technologies.

What you'd actually do

  1. Develop and maintain mathematical models to value and hedge financial transactions, from vanilla products to complex derivatives
  2. Improve algorithmic trading strategies and promote advanced electronic solutions for clients worldwide
  3. Collaborate with risk functions to develop models for market and credit risk across various business lines
  4. Build methodologies and infrastructure to implement models in production environments
  5. Write clear documentation covering model specifications and implementation testing

Skills

Required

  • Ph.D or Master’s degree in financial engineering, computer science, mathematics, sciences, statistics, econometrics, or other quantitative fields
  • 2 years of experience in a related quantitative or analytical role
  • Strong quantitative, analytical, and problem-solving skills
  • Solid background in calculus, linear algebra, probability, and statistics
  • Proficiency in at least one object-oriented programming language (e.g., C++ or Java) and strong skills in Python
  • Knowledge of data structures, algorithms and AI technologies
  • Ability to work independently and in a team environment
  • Strategic and creative thinking in problem-solving
  • Excellent verbal and written communication skills, with the ability to engage and influence stakeholders

Nice to have

  • Experience with markets and general trading concepts and terminology
  • Knowledge of financial products in commodities and other macro asset classes
  • Background in computer algorithms, Python, and specialization or significant coursework in network engineering
  • Understanding of options pricing theory, trading algorithms, financial regulations, stochastic calculus, machine learning, or high-performance computing

What the JD emphasized

  • regulatory requirements

Other signals

  • Develop and maintain mathematical models
  • Improve algorithmic trading strategies
  • Build methodologies and infrastructure to implement models in production environments
  • Knowledge of data structures, algorithms and AI technologies
  • machine learning