Quantitative Developer — Build Trading Research Tools

Long Ridge Partners; New York (NY); Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Hybrid work model

Generous paid time off

Wellness reimbursements

Job summary

Long Ridge Partners seeks a Quantitative Developer in New York to advance the firm’s research framework and build production-quality tools for researchers daily. You will work closely with the quantitative research group to extend capabilities and support trading strategies.

Ideal candidates bring strong Python experience (3+ years) and familiarity with NumPy, Pandas, and Polars, plus Bash scripting. You will engage with engineers, researchers, and traders across a distributed team in a

Qualifications

• BS in Computer Science or related field from a top program.
• Strong Python programming in production environments (≥3 years).
• Experience with NumPy, Pandas, Polars for data processing.
• Familiarity with Bash or similar scripting languages.
• Experience translating researcher needs into production-grade software.

Responsibilities

• Develop and enhance the quantitative research framework and tools.
• Provide day-to-day support to the on-site quantitative research team.
• Collaborate with researchers and traders to translate needs into reliable software.
• Work across the stack from Python tooling to performance-critical components.

Skills

Python

NumPy

Pandas

Polars

Bash

Workflow management

Communication skills

Education

Bachelor's degree in Computer Science

Master's degree (preferred)

Tools

NumPy

Pandas

Polars

Job description

Long Ridge Partners seeks a Quantitative Developer in New York to advance the firm’s research framework and build production-quality tools for researchers daily. You will work closely with the quantitative research group to extend capabilities and support trading strategies.

Ideal candidates bring strong Python experience (3+ years) and familiarity with NumPy, Pandas, and Polars, plus Bash scripting. You will engage with engineers, researchers, and traders across a distributed team in a