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Asset Management - Investment Platform Trading Analytics & Strategy (GFICC) - Executive Director

Pay
Pay not listedSimilar roles state $118K–$195K
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Automate trading workflows to reduce manual steps, focusing on credit and securitized products

  • Lead research into market microstructure and liquidity across rates, credit, FX and commodities

  • Advise traders and portfolio managers on execution strategy and market impact trade-offs

  • Build and maintain dashboards, TCA frameworks and execution quality tools

  • Coordinate trading, portfolio management and technology teams to deliver analytics projects

From the employer’s posting
Work directly with traders to automate workflows, reduce manual intervention
Lead research into market microstructure, price formation, and liquidity dynamics across rates, credit, FX, and commodities
Act as a subject matter expert for traders and portfolio managers, providing data-driven recommendations on execution strategy
Build and maintain dashboards, TCA frameworks, and execution quality tools
Coordinate across trading, portfolio management, and technology teams to deliver end-to-end analytics solutions
Apply at JPMorgan Chase

Posting record

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Open 4 monthsWe first saw this posting 132 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jul 1, 2026132 days ago
Recorded sightings
266
Last seen by us
Nov 11, 2026
Employer says posted
Jun 22, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$195K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,817 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 132

Up longer than most. Similar jobs usually come down between day 8 and day 59.

Well past JPMorgan Chase’s usual: its jobs come down by about day 15.

From 11,367 similar postings that came down, and 967 of JPMorgan Chase’s. Coming down is not always a hire.

JPMorgan Chase is hiring

366 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Scientist hiring has slowed
  • Takes jobs down at a usual pace
  • 3% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Matplotlib
  • NumPy
  • pandas
Where the posting names them
Required qualifications, skills and capabilities: - Python Proficiency: Strong hands-on experience with Python for quantitative research, including data manipulation (pandas, NumPy), visualization (matplotlib, seaborn), and performance-oriented coding practices. - Market Data & Databases: Demonstrated ability to work with tick-level and transactional market data using high-performance query tools and financial databases.

Your next step

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About JPMorgan Chase

People
About 318,512 in 2025.Annual report (SEC Form 10-K)
Company
Listed as JPM.
Layoff notices
Notices this year and last cover 152 people. The latest was filed March 23, 2026.State WARN notices

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 6% over the last 6 weeks compared with the 6 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 1,408, the most 2,964, and the latest week had 2,126.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

The Trading Research team delivers quantitative analysis across equites, fixed income, credit, currencies, and commodities to drive execution excellence and systematic trading innovation. Our work spans transaction cost analysis (TCA), execution optimization, and automation of trading workflows — all underpinned by a global analytics platform shared across teams in New York, London, Hong Kong, and Mumbai. We partner closely with trading desks to translate quantitative insight into tangible improvements in execution quality and operational efficiency.

Job summary:

As an Investment Platform Quantitative Researcher Executive Director on the Asset Management Investment Platform Trading Research team Executive Director on the Asset Management Investment Platform you will take a leading role in shaping and executing strategy and automation across GFICC asset classes. You will lead cross functional projects for our investment platform and provide execution consultancy to our clients. 

Job responsibilities:

  • Execution Optimization & Automation Work directly with traders to automate workflows, reduce manual intervention, and improve the speed and consistency of execution — with a particular focus on liquidity-constrained or bespoke instruments such as credit and securitized products.
  • Quantitative Trading Research Lead research into market microstructure, price formation, and liquidity dynamics across rates, credit, FX, and commodities. Identify actionable signals and develop statistical frameworks to optimize execution timing, venue selection, and order routing.
  • Execution Consultancy Act as a subject matter expert for traders and portfolio managers, providing data-driven recommendations on execution strategy. Advise on optimal approaches to balancing market impact and transaction costs across varying liquidity regimes and instrument types.
  • Trade Analytics & Reporting Build and maintain dashboards, TCA frameworks, and execution quality tools that provide transparency into trading performance, market impact, and slippage. Develop both scheduled and bespoke reporting to support desk leadership and portfolio management.
  • Cross-functional Leadership Coordinate across trading, portfolio management, and technology teams to deliver end-to-end analytics solutions. Define requirements, manage delivery timelines, and ensure outputs are practical and embedded in day-to-day trading workflows.

     

Required qualifications, skills and capabilities: 

  • Python Proficiency: Strong hands-on experience with Python for quantitative research, including data manipulation (pandas, NumPy), visualization (matplotlib, seaborn), and performance-oriented coding practices.

  • Market Data & Databases: Demonstrated ability to work with tick-level and transactional market data using high-performance query tools and financial databases.

  • GFICC Market Knowledge: Solid understanding of fixed income and FX market microstructure, execution dynamics, liquidity provisioning, and the mechanics of electronic and voice trading.

  • Execution & Algorithms: Practical knowledge of algorithmic execution, smart order routing, and the quantitative drivers of transaction costs in fixed income or currency markets.

  • Stakeholder Communication: Proven ability to translate complex quantitative outputs into clear, actionable recommendations for non-technical audiences including traders and senior business stakeholders.

  • Collaborative Development: Experience working in team-based development environments using version control systems (Git) and structured code review processes.

  • Applied Machine Learning: Familiarity with ML techniques relevant to trading research, including supervised/unsupervised learning, reinforcement learning, or NLP applied to financial data.

Source details

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Location & working pattern

New York, NY, United States

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