Quantitative Research Engineer

Numeus is a diversified digital asset investment firm built to the highest institutional standards, combining synergistic businesses across Alpha Strategies, Trading, and Asset Management.

Numeus was founded by successful executives with decades of experience across the finance, blockchain and technology industries, with a shared passion for digital assets. Our values are grounded in an open approach based on connectivity, collaboration, and partnerships across the digital asset ecosystem. People and technology are at the core of everything we do.

• Collaborate with quantitative researchers to understand their workflow, challenges, and requirements, and provide technical solutions to improve their research productivity
• Design, develop, and maintain software tools, platforms, and frameworks that enhance the efficiency and effectiveness of research activities, including data gathering, preprocessing, analysis, and model development
• Identify and implement advanced data processing techniques, algorithms, and statistical methods to optimize research workflows and enhance data analysis capabilities
• Leverage your expertise in software engineering, data engineering, and machine learning to build scalable and robust systems that facilitate large-scale data analysis and experimentation
• Conduct code reviews, provide technical guidance, and mentor junior research engineers to ensure code quality, maintainability, and adherence to best practices
• Collaborate with cross-functional teams, including quantitative researchers, data scientists, and engineering professionals, to integrate research tools and systems into the existing infrastructure
• Assist in the evaluation and implementation of third-party tools, libraries, and data sources that can enhance the research process
• Participate in research discussions, contribute ideas, and provide technical expertise to improve research methodologies and strategies
• Contribute to the development and maintenance of documentation, user guides, and training materials related to research tools and processes

• 4+ years experience working in close partnership with quantitative researchers to develop, deploy and maintain quantitatively-driven alpha strategies. Previous experience at a quantitative hedge fund is strongly preferred. 
• Masters or Ph.D. in Computer Science, Engineering, Data Science, or a related field
• Exceptional Python programming skills, with a focus on building scalable and efficient systems
• Experience with graph (DAG) representation, analysis, and processing using tools like NetworkX
• Experience with open source distributed computing tools in Python, such as Dask or Ray
• Proficiency in data processing, analysis, and visualization leveraging best-in-class open source tools, libraries, and frameworks (e.g., Pandas, Plotly, SciPy) 
• Solid understanding of statistical modeling, machine learning techniques, and their practical applications in quantitative research
• Solid understanding of the differences between L1, L2 and L3 market tick data
• Experience with AWS, Linux and Docker
• Excellent problem-solving skills and the ability to design practical solutions to complex research challenges
• Strong communication and collaboration skills to effectively work with cross-functional teams and translate research requirements into technical solutions
• Experience in recruiting, mentoring, and guiding junior team members is preferred
• Ability to travel periodically between our offices in London, NYC, and Zug, Switzerland

Are you keen to work in a well-resourced startup environment, where your ideas, experience, and drive to find creative solutions makes a difference? We’d like to hear from you.

The base salary for this role is anticipated to be between $150,000 and $225,000. This anticipated base salary range is based on information as of the time this post was created. This role may also be eligible for additional forms of compensation and benefits, such as a discretionary bonus, health, dental and other benefits plans. Actual compensation will be carefully determined based on a number of candidate factors, including their skills, qualifications and experience.