Job Description

Quantitative Trading & Research (QTR) is an expert quantitative modeling group in J.P. Morgan, as well as a leader in financial engineering, data analytics, statistical modeling and portfolio management. As a global team, QTR partners with traders, marketers and risk managers across all products and regions, contributes to sales and client interaction, product innovation, valuation and risk management, inventory and portfolio optimization, electronic trading and market making, and appropriate financial risk controls.

As Associate / Vice President within the QTR eTrading team, you will be responsible for performing research that helps improve the firm’s equities electronic execution business. Along with 10+ researchers globally, you will get the opportunity to partner with sales and marketing, product and technology teams across all regions. In addition, QTR provides on-the-job training, intensive internal classroom training, and online courses, all given by our experienced quants.

We make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as any mental and physical health needs or particular family considerations.

If you are passionate, curious and ready to make an impact, we are looking for you.

Job Responsibilities:

• Developing mathematical models for algorithmic execution strategies, both for single stock and portfolios

• Designing state-of-the-art models for limit order placement, and order routing between venues

• Developing quantitative tools to analyze order flow and suggesting methods for improving execution performance

• Carrying out market microstructure research and writing white papers

Required Qualifications, Skills and Capabilities

• You should have prior experience in one or more of the following:

  • Handling high frequency data/big data and developing statistical and/or machine learning models on the same

  • Pre/post trade analytics (including market microstructure research) for execution algorithms

  • Short term price predictive, alpha and portfolio optimization models

• You demonstrate quantitative and problem-solving skills as well as research skills

• You are keen to explore new research in algorithmic trading and assess its applicability to business problems

• You bring computer programming experience such as use of Python and/or C++ in a substantial project in an academic/commercial environment

• You’re enthusiastic about knowledge sharing and collaboration

• Your excellent communication skills, both verbal and written, can engage and influence partners and stakeholders

Preferred Qualifications, Skills and Capabilities

• Prior experience in q/kdb programming

• Orientation towards careful system and solution design and implementation

• Robust testing and verification practices

• Familiarity with LLM-based productivity tools and features

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.