Quantitative Software Engineer – Quantitative Components

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

• Prototype implementations of new research ideas alongside researchers
• Quantify how your component changes affect trading models and discuss the results with researchers and engineers
• Take ownership of a slice of the shared modelling infrastructure and evolve it
• Pick up several research domains quickly to understand what each team needs from the platform

What they ask for

Required

• Software engineering
• Quantitative analysis
• Statistical methods
• Convex optimisation
• Numerical methods
• Clear communication
• 1+ year of experience

Preferred

• Performance optimisation
• Knowledge of finance and market structure

Education

BS in computer science, applied maths or another technical or quantitative field

Experience

At least 1 year; 5–10 years preferred in software engineering and quantitative analysis

How to prepare

• Write a convex optimisation problem (for example a constrained portfolio) with a modern solver and test its edge cases
• Profile and speed up a numerical Python routine, and record the gains
• Review statistics fundamentals: regression, bias-variance, hypothesis testing
• Build a small, well-tested library with continuous integration to show engineering discipline

What to study

• Linear Algebra, Optimisation and Numerical Methods
• Probability, Statistics and Financial Data
• Python for Quantitative Finance
• Professional Quant Practice
• Market Microstructure and Execution

Apply

Read the full posting on Two Sigma’s site before applying: requirements, location and pay can change after we check them.

View the posting on Two Sigma’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Two Sigma and doesn’t handle applications.

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