Quantitative Developer, Graduate
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Before you apply
LocationLondon, United Kingdom
Typefull-time
SeniorityEntry
DepartmentIMR
Company size4+ people
PostedSep 25, 2026 · 1mo ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
1st class undergraduate degree in Computer Science
Completed a relevant internship with strong skills in Python
Hands-on experience with building and deploying data pipelines
Familiarity with modern infrastructure (CI/CD, Kafka, Airflow)
Excellent communication and collaboration skills
Detail orientated, with a commitment to best engineering practices
The ability to prioritise, plan and deliver to projects in a timely manner
Postgraduate qualifications are preferred but not necessary
Academic or internship exposure to trading systems for commodity derivatives
Experience of working closely with researchers and portfolio managers
Basic knowledge of statistical modelling in a financial context
Exposure to parallel & concurrent processing, e.g. Dask
Familiarity with containerised cloud development, deployment and management
Skills
Python
CI/CD
Kafka
Airflow
Dask
Docker
Kubernetes
AWS
About Winton
Winton is a research-based investment management company with a specialist focus on statistical and mathematical inference in financial markets. The firm researches and trades quantitative investment strategies, which are implemented systematically via thousands of securities, spanning the world’s major liquid asset classes. Founded in 1997 by David Harding, Winton today manages assets for some of the world’s largest institutional investors.
We employ ambitious professionals who want to work collaboratively at the leading edge of investment management.
About the role
We are seeking a talented quantitative developer to join the Investment Management & Research group at Winton. The role sits within our Fundamental Commodities strategy, where you will work closely with the Senior Portfolio Manager. Within our collaborative environment, you will help design and build the systems and tools that underpin the firm’s trading and research.
Your focus will initially be on software development: adding functionality required for new trading strategies and maintaining the existing signal pipeline. Over time, you will become more involved in research, eventually running projects independently.
Your responsibilities will include:
•
Design, implement and maintain pipelines for the ingestion of new datasets for systematic trading strategies
•
Partner with the Portfolio Manager and senior developers to deploy new trading strategies
•
Maintain and improve trading infrastructure, data visualisations and data validation in a production environment
What we’re looking for:
•
1st class undergraduate degree in Computer Science
•
Postgraduate qualifications are preferred but not necessary
•
Completed a relevant internship (e.g. software engineering, quantitative development, or a related placement), with strong skills in Python
•
Hands-on experience with building and deploying data pipelines, gained through internship, academic, or personal projects
•
Familiarity with modern infrastructure (CI/CD, Kafka, Airflow)
•
Excellent communication and collaboration skills
•
Detail orientated, with a commitment to best engineering practices
•
The ability to prioritise, plan and deliver to projects in a timely manner
What would be useful:
•
Academic or internship exposure to trading systems for commodity derivatives, ideally within a systematic hedge fund
•
Experience of working closely with researchers and portfolio managers
•
Basic knowledge of statistical modelling in a financial context
•
Exposure to parallel & concurrent processing, e.g. Dask
•
Familiarity with containerised cloud development, deployment and management (Docker, Kubernetes, AWS)
Equal Opportunity Workplace
We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.