Jobs
The Quantitative Trading & Research (QTR) e Trading Team design and implement trading algorithms to integrate client solutions across various functions. This team contributes to the design and implementation of the algorithmic trading products where they integrate quantitative research and data analytics for client solutions across various functions in electronic trading.
Our team partners with the electronic trading desk and technology teams to develop sophisticated mathematical models, cutting-edge methodologies and infrastructure to improve the performance of algorithmic trading strategies and promote advanced electronic solutions to our clients worldwide. The Quantitative Researcher function within the QTR e Trading team works closely with other quant researchers, the algo development team and the product team to deliver global solutions for our clients.
As a Vice President in the QR e Trading team, you will lead the design and implementation of the algorithmic trading platform, integrating quantitative research, data analytics, and client solutions across various functions within e Trading. You will apply optimization techniques to enhance trade scheduling for both single stocks and portfolio trading in the algo engine. Collaborating with researchers in the QR team and working closely with the electronic trading product and algo development technology teams, you will have the opportunity to guide and shape the direction of the platform.
Job Responsibilities
- Lead the QR e Trading team locally to drive algo execution product research and development
- Partner closely with the product team and trading desks to design and build client centric solutions
- Collaborate with quant researchers and trading desks to refine models and strategies that enhance our algorithm performance
- Build robust algorithms on cutting-edge execution platform by collaborating closely with our technology partners to integrate quantitative models and deliver optimal solutions within the algo trading engine
- Support diagnosis of trading decisions by explaining model and algorithm behavior, conducting scenario analyses, and developing quantitative tools and data analytics.
- Validate production implementations for fidelity with the original research specifications.
Required qualifications, capabilities, and skills
- Masters in STEM subjects such as computer science, engineering, mathematics/statistics, physics, operations research
- 5 years of experience in position(s) on algorithmic execution strategies or trading platforms
- Knowledge of cash equity markets, microstructure and market impact.
- Relevant experience in quantitative research, electronic trading, or related fields.
- Advanced knowledge of mathematics and statistics (probability theory, time series, econometrics, causal inference).
- Exceptional analytical, quantitative and problem-solving skills to break down complex high dimensional decision variable problems into smaller tractable subproblems.
- Strong written and verbal communication skills, with proven ability to communicate complex research ideas clearly and precisely, both in writing and verbally.
- Experience with kdb+/q.
- Experience coding in Java or C++
Preferred qualifications, capabilities, and skills
- Experience with Python, AWS and/or other database/data processing technologies
- Experience with alpha researches and their application in algo executions
- Experience with stochastic control, stochastic/numerical optimization techniques relevant to single stock or portfolio trading strategies
- Experience with writing production grade implementations for trading systems in Java/C++
- Familiarity with machine learning and deep neural networks.
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About JPMorgan Chase

JPMorgan Chase
PublicJPMorgan Chase & Co. is an American multinational banking institution headquartered in New York City and incorporated in Delaware. It is the largest bank in the United States, and the world's largest bank by market capitalization as of 2025.
300,000+
Employees
New York City
Headquarters
$500B
Valuation
Reviews
3.8
10 reviews
Work-life balance
3.2
Compensation
4.1
Culture
3.8
Career
3.0
Management
2.5
65%
Recommend to a friend
Pros
Good benefits and compensation
Supportive and collaborative environment
Flexible work arrangements
Cons
Long hours and heavy workload
Management issues and lack of direction
High stress during peak times
Salary Ranges
41 data points
Mid/L4
Senior/L5
Mid/L4 · Applied AI ML Associate
2 reports
$188,500
total per year
Base
$145,000
Stock
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Bonus
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$182,000
$195,000
Interview experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer rate
40%
Experience
Positive 20%
Neutral 80%
Negative 0%
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1
Application Review
2
HireVue Video Interview
3
Recruiter Screen
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Superday/Panel Interview
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Final Interview
6
Offer
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