Quantitative Developer

Jay Analytix; New York (NY); Hybrid; USD 120,000 - 150,000; Full time

Benefits offered by this job

Hybrid work arrangement

Collaboration with trading and risk teams

Job summary

Jay Analytix in New York is looking for a Quantitative Developer with a deep understanding of quantitative finance and advanced proficiency in Python. You will work on developing and implementing financial models critical for trading and risk management decisions in a hybrid environment.

The ideal candidate will possess at least 7 years of industry experience, knowledge in capital markets, and the ability to translate complex models into robust, production-grade code. This position offers opportunities to work on impactful systems within major financial hubs.

Qualifications

• Minimum 7 years of experience in a quantitative development or related role.
• Strong understanding of derivatives, fixed income, and capital markets.
• Solid grounding in probability, stochastic processes, and statistics.

Responsibilities

• Develop and implement pricing and risk models for derivative products.
• Translate quantitative models into production-quality Python code.
• Perform backtesting and simulation of trading strategies.

Skills

Quantitative development experience

Capital markets knowledge

Advanced Python

Data analysis

Familiarity with SQL

Tools

NumPy

Pandas

SciPy

C++ (nice to have)

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.