VP Quant Developer - Fixed Income Research & Data

JPMorgan Chase

New York (NY)

On-site

USD 170,000 - 285,000

Full time

14 days+

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Job summary

A leading financial services company is looking for a Quantitative Developer to support alpha generation through data analysis and code development. The role involves collaborating with quant researchers and investors to develop financial analytical code, managing the software development lifecycle, and enhancing data infrastructure. Strong skills in Python, familiarity with fixed income markets, and proficient use of various data tools are essential for success in this dynamic role.

Qualifications

  • Strong coding skills in Python including libraries like pandas and polars.
  • Familiarity with fixed income markets and data analysis.
  • Ability to adapt to changing market conditions.
  • Familiarity with SQL databases and data APIs.
  • Proficiency with tools like git and bitbucket.
  • Good understanding of IDEs such as IDEA or vscode.
  • Familiarity with AWS technologies like S3 and airflow.

Responsibilities

  • Develop code to analyze financial data and provide insights.
  • Assist quant researchers in developing production quality code.
  • Manage software development lifecycle and repository.
  • Improve data infrastructure for alpha signal generation.

Skills

Strong coding skills in Python
Familiarity with fixed income markets
Ability to adapt to rapidly changing market conditions
Familiarity with SQL databases
Proficiency with software repository tools such as git
Good understanding of professional IDEs
Familiarity with AWS technologies

Job description

A leading financial services company is looking for a Quantitative Developer to support alpha generation through data analysis and code development. The role involves collaborating with quant researchers and investors to develop financial analytical code, managing the software development lifecycle, and enhancing data infrastructure. Strong skills in Python, familiarity with fixed income markets, and proficient use of various data tools are essential for success in this dynamic role.
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