Quantitative Developer, Graduate

2 нед. назад

ВеликобританияJuniorOnsite

pythonsoftware development

Develop software and tools for trading and research in a quantitative investment management team, expanding into research projects over time.

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, 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.
We are seeking a talented quantitative developer to join the Investment Management & Research group at . 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.

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

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

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