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Qube Research & Technologies

2027 - Internship, Business Data Analytics

London

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Eligibility

  • Penultimate or final-year students completing a bachelor’s or master’s degree.

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Internship program targeting penultimate or final-year students to work in business data analytics, including applied AI engineering, applied data science, and investment analytics at a quantitative investment firm.

Responsibilities

  • Translate business questions into analytical approaches, research and evaluate methods, and develop prototypes for integration with developers.
  • Combine, structure and validate datasets across firms, teams and people; collect and analyse financial, market and portfolio data.
  • Build dashboards monitoring investment performance, portfolio exposures, risk metrics, and market trends.
  • Support investment research through quantitative analysis; communicate findings through clear visualisations and explanations for non-technical stakeholders.
  • Assess accuracy and reliability, documenting assumptions and limitations.
  • Prototype and test AI agents for document information extraction, research summaries, and recurring reports.

Requirements

  • Studying towards, or recently completed, a degree in Computer Science, Statistics, Data Science, Mathematics or another STEM discipline with relevant practical experience.
  • Strong Python skills, clean, well-structured code, and experience cleaning, joining and modelling data from multiple sources.
  • Intellectual curiosity about business, data and technology; strong analytical and problem-solving skills and a consulting mindset.
  • Evidence of taking an open-ended problem from idea to working solution through projects, coursework, research or internships.
  • Clear communication, initiative, and organisation, with confidence working through undefined requirements.
  • Track-specific skills relevant to Applied AI Engineering, Applied Data Science, or Investment Analytics.

Skills

  • Python
  • LLMs
  • agents
  • retrieval
  • statistical methods
  • machine learning
  • graph-based methods
  • dashboarding
  • communication
  • data cleaning
  • data modelling
  • SQL
  • AWS
  • Dash
  • FastAPI
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