Quant Research Engineer

Quant Research Engineer

Job Description

[c. £200-300k Comp Package (or equivalent) | Hybrid Working - 3 Days in Office]

Are you a research-focused engineer with a passion for building and optimising cutting-edge quantitative research infrastructure? Our client, a leading systematic buy-side crypto trading firm, is looking for an experienced Quantitative Research Infrastructure Engineer to drive efficiency and scalability across their research workflows. This role sits at the core of the firm’s data-driven investment process, working closely with researchers to develop powerful tools, streamline data processing, and enhance computational capabilities for alpha discovery...

Key Responsibilities

• Enhance research workflows by designing and maintaining scalable data pipelines, preprocessing frameworks, and large-scale simulation tools
• Collaborate with quantitative researchers to understand complex research needs and implement software solutions that improve productivity and data analysis
• Develop high-performance computing solutions, leveraging distributed computing frameworks such as Dask or Ray to process large-scale datasets efficiently
• Optimise data engineering processes, including graph-based data analysis with tools like NetworkX and best-in-class statistical libraries (e.g., Pandas, SciPy, Plotly)
• Ensure seamless research infrastructure integration, working across teams to align technology with research objectives and improve overall system performance
• Drive best practices in software engineering, conducting code reviews, mentoring junior engineers, and ensuring robust, scalable systems
• Contribute to quantitative strategy development, providing technical expertise to refine research methodologies and execution models

What You Bring...

• 4+ years of experience in quantitative research engineering, preferably within a hedge fund or systematic trading environment
• 3+ years experience in advanced Python programming skills, with expertise in optimising performance and designing scalable computational systems
• Experience with Python-based distributed processing tools
• Strong background in data engineering, including experience with graph-based processing tools like NetworkX
• Understanding of financial market data, particularly L1, L2, and L3 market tick data
• Proficiency in cloud computing and infrastructure, with experience deploying research environments in AWS, as well as working with Linux and Docker
• Solid knowledge of statistical modelling and machine learning techniques relevant to quantitative research
• (Preferred) Experience mentoring junior engineers and contributing to hiring efforts
• (Preferred) Familiarity with the intersection of research infrastructure and alpha generation strategies

...

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