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Open nowPosted 23 days ago

Quantitative Analyst - Jersey City, NJ (Not a VP role)

Workable (global search)108,016 open roles

Where
Jersey City, NJ, United States
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Your applicationOpen nowQuantitative Analyst - Jersey City, NJ (Not a VP role)Workable (global search) · Jersey City, NJ, United States

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 23 days ago

Workable (global search) median: 7 days open

The posting

Role: Quantitative Analyst/Developer

Experience: 5 to 8 years (not a VP role)

Employment: W2 (USC and GC only)

Location: Jersey City, NJ

Work mode: Hybrid

Primary Requirement

  • Design, develop, and maintain research and prototype development platforms, including database architecture, stored procedures, query optimization, and performance tuning.
  • Develop, test, deploy, and support quantitative model prototypes, analytical tools, and automated workflows; monitor daily scheduled jobs and production processes.
  • Perform NSCC margin and stress testing model monitoring, performance reporting, and analysis to support risk management activities.
  • Collaborate with quantitative researchers and risk teams to support model development, research initiatives, and data analysis needs.
  • Translate business requirements into technical specifications and independently design, build, test, and document small-to-medium-scale projects.
  • Serve as a liaison between Financial Engineering, Market Risk, Risk Technology, and application development teams, facilitating effective communication between business and technical stakeholders.

Qualification

  • Master's degree in a quantitative discipline and at least 5 years of experience in quantitative development, database development, or financial model implementation.
  • Strong programming skills in Python, including experience with libraries such as NumPy, Pandas, SciPy, SQLAlchemy, pyodbc, subprocess, logging, and Snowpark.
  • Advanced knowledge of SQL and relational databases, with hands-on experience in database design, stored procedure development, query optimization, and performance tuning; Snowflake experience strongly preferred.
  • Proficiency with Linux, Git, Bitbucket, and modern software development practices.
  • Experience developing, implementing, or supporting financial and quantitative models, with familiarity with financial engineering concepts and terminology.
  • Strong analytical, communication, and problem-solving skills, with the ability to work independently, translate business needs into technical solutions, and effectively bridge communication between quantitative researchers and software developers.
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