Summer Data Science Intern in London: Data, ML & Markets

Cooper & Hall Limited; Greater London; Hybrid; GBP 20,000 - 27,000; Full time

Benefits offered by this job

Accommodation

Lunch provided

Barista bar

30 days annual leave pro-rated

Central London office near multiple交通

Weekly intern activities

Job summary

G-Research in London offers a 10-week Summer Research Programme for interns to gain insight into data science within a leading quantitative research firm. The role runs 09:00-17:30, based in Central London, and emphasizes collaboration with world-class researchers and engineers.

You will apply techniques in data blending, statistics and machine learning to support dataset exploration, validation and visualization, while helping build tooling used across the company.

Qualifications

• Currently enrolled in an undergraduate, Master's or PhD program in a quantitative field.
• Strong problem-solving and critical thinking abilities.
• Experience applying statistics to real-world datasets.
• Experience using Python for exploratory data analysis and visualization.

Responsibilities

• Support data exploration, enrichment and creation of new datasets for research.
• Help scale and automate data analysis, validation and visualization.
• Contribute to building tooling for data science initiatives across the company.
• Collaborate with data scientists and financial experts in a multi-disciplinary team.

Skills

Quantitative background

Problem solving

Statistical concepts

Python/Data analysis

Communication skills

Interest in financial markets

Independent research

Education

Undergraduate/Master's/PhD student in quantitative field

Tools

GitHub profile

Kaggle profile

ML model development

NLP interest

Job description

G-Research in London offers a 10-week Summer Research Programme for interns to gain insight into data science within a leading quantitative research firm. The role runs 09:00-17:30, based in Central London, and emphasizes collaboration with world-class researchers and engineers.

You will apply techniques in data blending, statistics and machine learning to support dataset exploration, validation and visualization, while helping build tooling used across the company.