High Yield Fixed Income Pricing & Analytics Analyst

J.P. Morgan; New York (NY); On-site; USD 90,000 - 150,000; Full time

Benefits offered by this job

Comprehensive health care

Retirement savings plan

On-site wellness facilities

Job summary

J.P. Morgan is seeking an Analyst/Associate in its High Yield Fixed Income team in New York. The role focuses on independent pricing and analytics for millions of instruments, using real-time market data and advanced modeling to support clients globally.

You will work on market monitoring, pricing updates, and development of ML-based improvements while collaborating with trading desks and research teams to enhance pricing accuracy and speed.

Qualifications

• Strong understanding of fixed income products and data science fundamentals.
• Strong quantitative skills and ability to build pricing models.

Responsibilities

• Generate daily valuations across multiple market closes with data collection and price generation.
• Monitor markets and provide real-time pricing updates.
• Develop and maintain statistical and machine learning models to improve pricing and QC.
• Build pricing methodologies and infrastructure to increase valuation accuracy and speed.
• Collaborate with trading desks, market participants and research teams on pricing insights.
• Respond to client questions via email, calls, or in person.
• Identify new areas of product growth by exploring ideas independently.

Skills

Fixed income analytics

Quantitative methods

Python

Excel VBA

Machine learning

Real-time pricing

Client interaction

Education

Bachelor's degree or higher in Financial Engineering/Quantitative Finance/Statistics/Economics

Tools

Python

SQL

Tableau/Data visualization

Job description

J.P. Morgan is seeking an Analyst/Associate in its High Yield Fixed Income team in New York. The role focuses on independent pricing and analytics for millions of instruments, using real-time market data and advanced modeling to support clients globally.

You will work on market monitoring, pricing updates, and development of ML-based improvements while collaborating with trading desks and research teams to enhance pricing accuracy and speed.