Quantitative Developer, Systematic Research Technology

Balyasny Asset Management

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
New York, NY
Salary
$200,000–$300,000 / yr
Posted
10 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $166k
This role $250k
$103k most similar roles pay here $321k

This role pays more than 90% of similar roles. Most pay $126,499–$206,336 — the shaded band above. At the midpoint, this role pays about $250k versus about $166k for comparable roles.

Based on 240 similar postings.

Employer

About Balyasny Asset Management

Balyasny Asset Management (BAM) is a global multi-manager hedge fund offering diversified investment strategies across equities, macro, commodities, and systematic trading.

Balyasny Asset Management currently has 45 open roles on FindRole.

Listed pay typically runs $175,000–$250,000 across 36 roles with salary data.

Most-posted roles

View all roles at Balyasny Asset Management

At a glance

TL;DR · Quantitative Developer, Systematic Research Technology

The Quantitative Developer - Systematic Research Technology joins the Systematic Research Technology team to build research and trading systems that enable investment teams to discover, evaluate, and deploy ideas. You will design and own software supporting data processing, model evaluation, and systematic trading while developing Python tooling for reproducible workflows and C++ components for performance-sensitive production systems. The role involves partnering with Quantitative Researchers to translate complex requirements into durable technical solutions while improving system reliability, observability, and testability. Candidates must possess strong programming skills in Python and/or C++, along with experience building data-intensive or production-critical systems. You will solve problems across the research-to-production lifecycle, making architecture decisions for systematic investing tools. Required expertise includes software engineering fundamentals, performance analysis, and debugging within a high-quality engineering environment.

What you'll do

  • Design and build software supporting quantitative research, data processing, model evaluation, and systematic trading.
  • Develop Python tools and libraries to improve research speed, reproducibility, and scalability.
  • Build and optimize C++ components for performance-sensitive and production-critical workflows.
  • Translate complex and ambiguous researcher needs into durable technical solutions.
  • Improve the reliability, observability, testability, and operational quality of research and production systems.
  • Diagnose complex technical problems across the research-to-production lifecycle and make architectural decisions.
  • Maintain high engineering standards through thoughtful design, code review, testing, and knowledge sharing.

What we're looking for

  • At least 5 years of hands-on development experience building and supporting production systems.
  • Strong experience in Python, C++, or both, with the ability to work productively across both languages.
  • Exceptional programming ability and strong software engineering fundamentals.
  • Sound judgment in software design, debugging, performance analysis, testing, and maintainability.
  • Experience building data-intensive, performance-sensitive, or production-critical systems.
  • Ability to communicate clearly and work effectively with various stakeholders including Portfolio Managers and Quantitative Researchers.
  • A degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field, or equivalent practical experience.
  • Experience with systematic investing, quantitative finance, Linux, distributed systems, GPUs, cloud infrastructure, or low-latency systems (preferred).

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