CIB QR – Quantitative Research – Equity Derivatives Analytics – Associate / Vice President



Technical Skills

  • Analytics
  • Apache Hadoop
  • Big Data
  • C++
  • Data Management
  • Data Science
  • Derivatives
  • Equities
  • Equity Derivatives
  • GitHub
  • Inventory Management
  • Java
  • Machine Learning
  • Microsoft Access
  • Operational Risk
  • Prototyping
  • Python
  • Risk Management
  • Statistics

Job Description

CIB QR – Quantitative Research – Equity Derivatives Analytics – Associate / Vice President

Equity Derivatives Analytics
The Equity Derivative Analytics team’s mandate is to bring data-driven decision making and automation to the Equity businesses, and to act as a culture carrier for modern data-driven business methods. The objective is to transform business practices, tools and infrastructure through data science.
  • Understand the business processes and their data
  • Industrialize availability of data
  • Develop data-driven decision making analytics through reports, analytics, predictions and optimization
  • Implement in a production setting
  • Provide strong control environment around data access, model risk and operational risk
    The team is expected to cooperate closely with the QR Equities Modeling and Technology teams and the other QR and Data functions to ensure leverage across the various data science efforts in JPMorgan.
  • Client analytics
  • Signal-driven idea generation
  • Data-driven trading decision making
  • Automatization of derivatives risk management, pricing and inventory optimization


The opportunity is to join our Hong Kong team as an Associate/Vice President. 
Key responsibilities include:
  • Perform large-scale analysis on our proprietary datasets
  • Identify new insights that drive feature modelling
  • Build prototype models with data pipelines that serve as roadmap to production
  • Make real-world, commercial recommendations through effective presentations to various stakeholders
  • Leverages data visualization to communicate data insights and results


The ideal candidate brings quantitative experience in the Equity business (products, models, market standards and business practices), combined with a background in machine learning techniques / statistics, and a curiosity to expand in this field. . Communication skills and drive are critical for the role as we expect the candidate not only to help defining future business practices but also to bring cultural change towards a modern data-driven approach to business.

Key qualifications:

  • A master’s or Ph.D. degree program in computer science, statistics, operations research or other quantitative fields

  • Strong technical skills in data manipulation, extraction and analysis

  • Fundamental understanding of statistics, optimization and machine learning methodologies

  • Mastery of software design principles and development skills using one of C++, Python, R, Java, Scala.

  • Confident in technology in particular around data management. Knowledge in KDB and Big Data solutions such as Hadoop/Spark, Hive etc advantageous

  • Previous practical experience in solving machine learning problems using open-source packages (such as sklearn). Experience in TensorFlow or other RL packages is advantageous.

  • Participation in KDD/Kaggle competition or contribution to GitHub highly desirable

  • Strong communication skills (both verbal and written) and the ability to present findings to a non-technical audience

Employment TypeFull-time
Education LevelMaster
JPMorgan Chase BankFinancial Services, Retail and Commercial Banking

1101-1102 & 1118-1120 Level 22 Tower 1, Grand Century Place, 193 Princess Edward Road West, Mongkok, Kowloon, Hong Kong

directions_walk18 mins walk from Prince Edward Station