Data Science Internship

About the role

Join G-Research's 10-week Data Science Internship in London to apply data science skills in quantitative finance. Work on data exploration, enrichment, and machine learning to support research initiatives in a collaborative environment.

Role Details

• 10-week summer internship from 2027-06-21 to 2027-08-27 in Central London.
• Working hours are 09:00 to 17:30, Monday to Friday.
• Gain insight into data science practices at a leading quantitative research firm.
• Support exploration, enrichment, and creation of datasets for research.
• Use data blending, statistical analysis, and machine learning methods.
• Build tools to enable data science initiatives across the company.

Responsibilities

• Investigate foundational questions and uncover market insights.
• Apply knowledge to scale and automate data analysis and validation.
• Collaborate with data scientists and financial experts in a multi-disciplinary team.
• Develop solutions adapting to a rapidly changing data landscape.
• Work on data strategy challenges within the firm.
• Gain exposure to multi-asset class systematic investing and big data development.

Candidate Requirements

• Current undergraduate, master's, or PhD student in a quantitative subject.
• Strong critical thinking and problem-solving skills.
• Comfortable applying statistical concepts to real-world data.
• Experience with Python for exploratory data analysis and visualization.
• Strong communication skills and interest in financial markets.
• Ability to work independently and eagerness to learn.

Desirable Skills

• Active GitHub or Kaggle profiles.
• Experience developing and refining machine learning models.
• Knowledge or interest in natural language processing.
• Proficiency in statistical data analysis.

Benefits

• Highly competitive compensation plus accommodation provided.
• Access to G-Research community and weekly intern activities.
• Lunch provided via Just Eat and dedicated barista bar.
• 30 days’ annual leave pro-rated.
• Informal dress code and excellent work/life balance.
• Central London office near multiple transport links.