Quantitative Systems Software Engineer

Two Sigma; Greater London; On-site; GBP 26,000 - 38,000; Full time

Job summary

Two Sigma in London is seeking student software engineers to join a general Software Engineering track and be matched to a specific team 2-3 months before start.

You will work on building infrastructure, ensuring the reliability of trading systems, and deploying models using open source and proprietary tools.

The role offers the chance to learn from leading engineers and contribute to scalable solutions powering data-driven investment strategies.

Qualifications

• Bachelor’s, Master’s or PhD in a technical or quantitative field.
• Experience with JVM languages such as Java, C++, Python, Ruby, or Perl.
• Experience in large-scale systems.
• Exceptional programming skills.
• Strong analytical, organizational, and interpersonal abilities.
• Open-minded in search for critical thinkers passionate about technology; finance experience not required.

Responsibilities

• Build underlying infrastructure used by other engineering teams, including distributed storage and cloud environments.
• Ensure reliability of mission-critical products and trading systems.
• Use open source and proprietary tools to build environments that test and deploy quantitative models.
• Build and maintain low-latency, high-performance infrastructure for executing trades.
• Scale infrastructure to ingest data from 10,000+ sources daily.
• Collaborate with Corporate teams to boost productivity and efficiency across the organization.

Skills

Java

C/C++

Python

Ruby

Perl

JVM languages

Large-scale systems

Analytical skills

Programming skills

Software quality

Education

Bachelor's/Master's/PhD in technical/quantitative field

Job description

Two Sigma in London is seeking student software engineers to join a general Software Engineering track and be matched to a specific team 2-3 months before start.

You will work on building infrastructure, ensuring the reliability of trading systems, and deploying models using open source and proprietary tools.

The role offers the chance to learn from leading engineers and contribute to scalable solutions powering data-driven investment strategies.