Description

You will build and scale technology platforms to support quantitative research and investment decision-making processes.

This role is hybrid.

Responsibilities

• Develop code libraries and distributed computing programs to generate analytics and user-friendly visualizations.
• Partner with product owners and quants to implement models and transition prototypes into production environments.
• Design, deliver, and maintain high-reliability, scalable proprietary models and algorithms.
• Implement standards for numerical library testing, code quality controls, and peer code reviews.
• Evaluate appropriate datasets, tools, and technology solutions to meet research requirements.

Required Skills

• 12+ years of progressive experience in software engineering and quantitative analysis.
• Expert proficiency in Python and PySpark.
• Strong coding skills in R and Java.
• Experience analyzing large datasets using PySpark, Pandas, Polars, and Cuml.
• Advanced mathematical knowledge in statistics, time-series analysis, asset pricing theory, and algorithms.
• Deep understanding of tradable financial instruments, including securities and derivatives, and capital markets.
• Experience with real-time, batch, and orchestration architectures.
• Strong Test-Driven Development (TDD) practices.
• Advanced degree in Computer Science, Math, or Financial Engineering.

Preferred Skills

• Front office software development experience within Asset Management, Hedge Funds, or Investment Banking.
• Experience building containerized applications and deploying to AWS or Microsoft Azure.
• Experience with web-based development and visualization for complex data sets.

Key Skills

Education

Any Graduate