Quantitative Developer

Jay Analytix INC.; New York (NY); Hybrid; USD 100,000 - 150,000; Part time

Benefits offered by this job

Hybrid work arrangement

Collaborative environment

Exposure to high-impact systems

Job summary

Jay Analytix INC. is seeking a Quantitative Developer based in New York, USA. This hybrid position involves building and implementing financial models and analytics used by trading and risk teams. The ideal candidate will have over 7 years of experience in quantitative development, with strong skills in Python and knowledge of capital markets and derivatives.

The successful candidate will work closely with traders and quants to ensure model accuracy and contribute to enhancing the analytics infrastructure. A collaborative environment bridging finance and technology awaits you.

Qualifications

• Minimum 7 years of experience in a quantitative development or related role.
• Capital markets domain experience is mandatory.
• Strong understanding of derivatives, fixed income, and capital markets.

Responsibilities

• Develop and implement pricing and risk models for derivative products.
• Translate quantitative models into production-quality Python code.
• Build libraries and tools for portfolio analytics, valuation, and risk measurement.

Skills

Quantitative Finance

Python

Probability and Statistics

Data Analysis

Capital Markets

Tools

NumPy

Pandas

SciPy

SQL

Job description

Quantitative Developer

Location: New York, USA — Hybrid Employment Type: Contract

About the Role

We are seeking a Quantitative Developer with strong expertise in quantitative finance and advanced proficiency in Python. This role focuses on building and implementing financial models, analytics, and pricing systems used by trading and risk teams. You will work at the intersection of finance and technology, translating sophisticated quantitative models into robust, production-quality code that directly supports trading and risk management decisions.

The ideal candidate brings deep capital markets domain knowledge, strong engineering discipline, and the ability to collaborate closely with quants and traders in a fast-paced, hybrid environment.

Key Responsibilities

• Develop and implement pricing and risk models for derivative products.
• Translate quantitative models (e.g., Black-Scholes) into production-quality Python code.
• Build libraries and tools for portfolio analytics, valuation, and risk measurement.
• Work closely with quants and traders to refine models and strategies.
• Perform backtesting and simulation of trading strategies.
• Validate financial models and ensure the accuracy of calculations.
• Contribute to the ongoing improvement of analytics infrastructure and code quality.

Required Skills

Quantitative & Finance (Core Focus)

• Minimum 7 years of experience in a quantitative development or related role.
• Capital markets domain experience is mandatory.
• Strong understanding of derivatives, fixed income, and capital markets.
• Solid grounding in probability, stochastic processes, and statistics.
• Hands‑on experience with pricing models, risk metrics, and financial data.

Technical

• Advanced Python, including NumPy, Pandas, and SciPy.
• Strong experience with data analysis and numerical computing.
• Familiarity with SQL and data handling.

Nice to Have

• Exposure to C++ for performance optimization.
• Experience working with quantitative research or trading desks.
• Familiarity with model validation practices and regulatory expectations.

What We Offer

• A hybrid work arrangement across major financial hubs in Canada and the USA.
• The opportunity to work on high-impact pricing and risk systems used by trading and risk teams.
• A collaborative environment that bridges quantitative finance and software engineering.

How to Apply

Qualified candidates are encouraged to submit a resume outlining relevant experience, including capital markets domain expertise and quantitative development work. We thank all applicants for their interest; only those selected for an interview will be contacted.