Front Office Trading Tech Intern — Python & Cloud (London)

United States Digital Space LLC

Greater London

On-site

GBP 22,000 - 30,000

Full time

14 days+

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Job summary

CCI is building a leading-edge analytics platform, seeking Front Office Software Engineering Interns to join the Global Data Science & Technology team in our London office.

This internship targets technically skilled students eager to build software that directly supports trading, analytics, and investment workflows, collaborating with Software Engineers, Data Scientists, and Commercial end users.

Qualifications

  • Bachelor's or Master's in Computer Science, Engineering, MIS or related field.
  • Strong programming experience in Python (Pandas, NumPy).
  • Familiarity with Git and software development best practices.
  • Interest in financial markets and trading systems.
  • Excellent communication in a fast-paced, collaborative environment.

Responsibilities

  • Contribute to development of front office software tools for real-time trading and analytics.
  • Collaborate with trading team to optimize pricing models and workflows.
  • Build Python-based microservices and APIs for data access and automation.
  • Create data visualization dashboards using Streamlit and KPI integration.
  • Develop cloud-native apps using AWS; work with Kubernetes and Kafka.
  • Support deployment automation with Git, Docker, Helm, and CI/CD pipelines.
  • Collaborate with Data Science to integrate ML analytics into workflows.

Skills

Python
Pandas
NumPy
Git
Communication

Education

Bachelor's or Master's in Computer Science/Engineering/MIS

Tools

AWS
Kubernetes
Kafka
Docker
Streamlit
CI/CD

Job description

CCI is building a leading-edge analytics platform, seeking Front Office Software Engineering Interns to join the Global Data Science & Technology team in our London office.

This internship targets technically skilled students eager to build software that directly supports trading, analytics, and investment workflows, collaborating with Software Engineers, Data Scientists, and Commercial end users.

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