Quantitative Developer - Equities
Role details
Job location
Tech stack
Job description
and researchers to support portfolio construction, trading, and monitoring workflows Design and implement risk and performance analytics for live portfolios Build scalable tooling for managing and analysing large, complex financial datasets Develop interactive, web-optimised visualisation components for internal users Take ownership of production systems, ensuring their reliability and performance Deliver features iteratively, incorporating user feedback to refine and improve applications Contribute to the evolution of the team's tech stack in response to changing business needs Your present skillset 3-5 years of experience as a software engineer, with recent front-office or fundamental investing exposure strongly preferred Expertise in Python for data-driven development Experience building front-end interfaces using React and TypeScript Familiarity with cloud platforms (e.g. AWS) is a plus Ability to manage multiple priorities and work directly with business users in an iterative, fast-paced environment Excellent communication and collaboration skills, both technical and interpersonal QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance. Responsibilities You will collaborate with portfolio managers and researchers to support portfolio construction, trading, and monitoring workflows. Additionally, you will design and implement risk and performance analytics for live portfolios and build scalable tooling for managing and analyzing large financial datasets.
Requirements
Python, React, TypeScript, Cloud Platforms, Data Analysis, Portfolio Construction, Risk Analytics, Performance Analytics, Web Optimization, Collaboration, Communication, Software Engineering, Iterative Development, Financial Datasets, Production Systems, User Feedback