Quant Research Intern: High-Impact ML in Finance (Summer)

Synthesis; Greater London; On-site; GBP 19,000 - 23,000; Full time

Benefits offered by this job

Arranged housing

Canteen allowance (Deliveroo)

Company-organised cultural events and暑

Job summary

Synthesis is seeking academically strong undergraduate students for a 10-week Quant Research Internship in 2027. You will analyze large financial datasets to feed into our end-to-end ML pipeline for equities, joining a small but established team with offices in London and New York.

You will collaborate on a structured data-driven project, receive mentorship, and gain exposure to our on-prem computational cluster and data library, along with feedback throughout the program.

Qualifications

• Pursuing an undergraduate degree in quantitative / STEM field from a top UK university.
• Expected to complete your undergraduate degree in 2027 (including candidates intending to continue directly into a master's degree).
• Familiar with probabilistic and statistical reasoning.
• Comfortable with Python ecosystem when dealing with data manipulation and regression tasks.
• Curious about the financial domain.
• Have an engineering mindset and a builder's mentality.

Responsibilities

• Work with large financial datasets to uncover insights feeding in our end-to-end ML pipeline for equities.
• Join a small, long-established team with offices in New York and London for a 10-week program.
• Deliver a finished, measurable research product within the internship timeframe.
• Collaborate in research discussions and engage with co-participants.

Skills

Python ecosystem

Probabilistic reasoning

Data analysis

Engineering mindset

Education

Undergraduate degree in quantitative / STEM field

Tools

Python

Job description

Synthesis is seeking academically strong undergraduate students for a 10-week Quant Research Internship in 2027. You will analyze large financial datasets to feed into our end-to-end ML pipeline for equities, joining a small but established team with offices in London and New York.

You will collaborate on a structured data-driven project, receive mentorship, and gain exposure to our on-prem computational cluster and data library, along with feedback throughout the program.