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London Area, United Kingdom

Internship

Hybrid

Intern

Commerzbank AG is an integrated Corporate and Investment Banking division that provides a wide range of commercial and investment banking products. They are seeking an Intern Data Scientist to join their Commodity Trading Desk, focusing on enhancing data availability, automation, and analytical capabilities through Python-based tools and AI-driven prototypes to improve trading strategies.

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Responsibilities

Design and develop Python-based tools and AI-driven prototypes to automate and streamline front office workflows
Build and maintain GUIs/dashboards that display continuously updated quotes and market information
Apply and promote Commerzbank Python code design rules and good software engineering practices, ensuring clean structure, readability, and maintainability in code written for and with colleagues on the desk
Demonstrate the use of agentic AI capabilities to support and optimize code development for team members, including using AI to refactor, document, and debug code
Implement and share optimization techniques for code performance and development workflows, helping colleagues improve the efficiency and robustness of their tools
Work closely with traders, quants, and other front office staff to identify relevant data sources, clarify requirements, and iterate on prototypes to ensure tools are aligned with real business needs
Document solutions, provide structured handovers, and support users in testing and integrating tools into their daily processes
Help the Commodities desk onboard and use AI tools available within the bank, including explaining available AI services and practical use cases, providing guidance on prompt design and best practices, highlighting limitations and control mechanisms, and offering ongoing support during initial adoption
Gather requirements from traders and other stakeholders and translate them into clear technical specifications
Communicate complex technical topics in an accessible manner to non-technical stakeholders. Onboard and support the various Commodity desks in the practical use of AI tools, including training sessions and demonstrations

Qualification

Required

Graduated in the last 12 months or graduating in 2026
The successful candidate is likely to be educated to degree level in Data Science, Computer Science, Statistics, Mathematics, Engineering, Physics, Quantitative Finance
Excellent numerical and analytical skills
Solid problem-solving abilities
Strong Python programming skills, including data processing, automation, API integration, and basic GUI/dashboard development
Practical experience with Large Language Models (LLMs) and LLM-based services, including: Prompt design and iterative refinement, Evaluation and comparison of model outputs, Integration of LLMs into data pipelines and tools
Ability to build software prototypes/Proofs of Concept (PoCs) and develop them into robust, stable tools
Familiarity with real-time or near real-time data processing from unstructured sources such as chat streams
Basic understanding of financial markets and commodities products sufficient to understand pricing information, quote structures, and trading workflows
Solid understanding of derivatives products at a theoretical and practical level
Experience with coding standards and version control; adherence to internal Python design principles
Ability to analyze loosely defined business problems and translate them into clear technical requirements
Structured approach to experimentation (e.g., prompt tuning, model selection, error analysis). Capability to design workflows that combine automated processing with appropriate human oversight to ensure data quality and control
Strong verbal and written communication skills
Team player
Ability to communicate complex technical topics in an accessible manner to non-technical stakeholders
Coordination with multiple desks and prioritization of tasks under time constraints