Quantitative Developer (Risk & PnL Analytics)

NJF Global Holdings Ltd; New York (NY); On-site; USD 180,000 - 230,000; Full time

Job summary

NJF Global Holdings Ltd in New York seeks a Quantitative Developer to join the Fixed Income & Macro business, working on front-office risk, pricing, PnL attribution, and portfolio analytics.

You'll sit with portfolio managers, traders and quant researchers, building real-time systems to understand exposures and daily PnL, with Python and performance-critical C++ components.

Qualifications

• Strong software engineering skills in Python (and C++ ideally).
• Ability to reason rigorously about exposures, risk metrics, and PnL.
• Background in front-office risk technology or related quantitative domains.
• Track record of building production systems, not just configuring or consuming someone else's.

Responsibilities

• Designing and building risk and PnL attribution systems for fixed income and macro portfolios.
• Developing tools for exposure analysis, VaR, and scenario/stress testing.
• Partnering with PMs, traders, and quant researchers to translate risk and pricing requirements into production systems.
• Working across the stack in Python, with performance-critical components in C++.

Skills

Python

C++

Risk analytics

Production systems

Job description

Total compensation: very flexible - dependent on seniority, expectations and performance

We're partnered with a leading global quantitative trading firm hiring a Quantitative Developer to join the Fixed Income & Macro business, working on front-office risk, pricing, PnL attribution, and portfolio analytics.

This is a front-office-facing role - you'll sit directly with portfolio managers, traders, and quant researchers, building the systems they use to understand exposures, risk, and daily PnL in real time.

This isn't a central risk-reporting function; it's embedded technology that shapes how the desk sees and manages its book.

What you'll work on:

• Designing and building risk and PnL attribution systems for fixed income and macro portfolios
• Developing tools for exposure analysis, VaR, and scenario/stress testing
• Partnering closely with PMs, traders, and quant researchers to translate risk and pricing requirements into production systems
• Working across the stack in Python, with performance-critical components in C++

What we're looking for:

• Strong software engineering skills in Python (and C++ ideally)
• Ability to reason rigorously about exposures, risk metrics, and PnL — you understand why numbers move, not just how to compute them
• Background in one of the following: front-office risk technology, quant research/development supporting an asset class or pod, risk-analytics vendor platforms, middle-office/product-control PnL production, treasury/funding technology, or computational domains such as derivatives pricing, numerical optimization, or simulation
• A track record of building production systems, not just configuring or consuming someone else's