Quantitative Developer
At a glance
Mid-level Data Science role at Jay Analytix. New York · contract.
Pay not stated Data Science salary
dataroles summary, based on the employer's posting.
What you'll do
- Develop pricing and risk models for derivative products used by trading and risk teams
- Convert quantitative approaches such as Black-Scholes into production-ready Python implementations
- Build portfolio analytics and valuation tools, including measures of financial risk
- Backtest and simulate trading strategies, then verify that model calculations are accurate
- Consult quants and traders on model and strategy changes while improving analytics tools and code quality
What you bring
- At least seven years in quantitative development or a related position
- Capital markets experience is mandatory, with knowledge of derivatives and fixed income
- Grounding in probability, stochastic processes and statistics, plus practical work with pricing models and risk measures
- Advanced Python with NumPy, Pandas and SciPy, along with data analysis and numerical computing experience
- SQL familiarity and experience handling data
Who this fits
This contract role suits a quantitative developer who brings capital markets knowledge and advanced Python skills. The position is hybrid in New York.
From the employer
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.
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