Quantitative Developer - Systematic

Tasks

• Development and implementation of systems as part of the London Quant Developer Team.
• Collaboration with software providers and use of proprietary workflow systems.
• Development of a software platform using a specialized suite of interfaces, including the industry-leading ERP software NetSuite.
• Work on a new engineering team in Shanghai that collaborates closely with portfolio managers to develop and advise on continuous trading algorithms.
• Improving and expanding the next generation of technologies while maintaining full familiarity with the infrastructure of the corporate ecosystem.
• Interaction and influence through standards and global initiatives, including pair programming with senior engineers.

technology stack

• Object C, C++, Python, and JavaScript for GUIs.
• Proprietary tools, mainly written in C++, as well as Python for version control.
• Big Data, including real-time data feeds and historical data.
• The systems run on Linux; most of the code is written in Python.
• Full-stack technologies: Java, Node.js, SQLAlchemy, Flask.
• Self-hosted Kubernetes clusters with Docker.
• 8 AWS accounts: 3 for development/staging and 5 for production.
• Docker Compose for continuous integration and deployment.
• Microservices architecture using modern enterprise management tools (Java, Node.js, Python).

Requirements

Essential

• At least 4 years of professional experience in software development, preferably with a focus on quantitative applications.
• Proficiency in C++ and Python, with experience developing complex, high-performance, fully testable models and application frameworks.
• Proficiency in working with object-relational databases, data processing pipelines, and deployment.
• Proficiency in using Linux platforms and Git.
• Strong knowledge of one or more relevant statistical techniques.

Advantages

• Experience in quantitative software development in a high-volume, low-latency environment, such as hedge funds, investment banks, or asset managers.
• Experience working with large-scale, low-latency/real-time distributed data streams.
• Experience in setting up task automation, code generation, and quality assurance using the appropriate tools.
• Familiarity with other important quantitative programming tools such as MATLAB, R, Mathematica, or Julia.
• Knowledge of modern data engineering practices, including data pipelines and ETL, testing, distributed storage and processing, and real-time processing.
• A strong understanding of financial markets and financial instruments.
• Experience working with UML-based data.
• Professional-level advanced knowledge, e.g., in databases and time series analysis.

We offer

• A competitive compensation package with short-term and long-term incentives, ranging from stock options to long-term incentive shares.
• Pension contributions amounting to 25%.
• Full or partial coverage (starting at 2,000 GBP) for medical, dental, and vision services, as well as life insurance and other benefits.
• Flexible working conditions.
• Access to a team of about 70 data and technology experts for occasional collaboration.
• Opportunity for interaction