At a Glance
- Tasks: Develop innovative tools and systems to enhance research productivity for quantitative researchers.
- Company: Numeus is a cutting-edge digital asset investment firm with a focus on collaboration and technology.
- Benefits: Enjoy competitive salary, bonuses, health benefits, and the chance to work in a dynamic startup environment.
- Why this job: Join a passionate team where your ideas can drive impactful solutions in the digital asset space.
- Qualifications: 4+ years of experience in quantitative research, strong Python skills, and a Master's or Ph.D. in a relevant field.
- Other info: Opportunities for travel between London, NYC, and Zug, Switzerland.
The predicted salary is between 108000 - 162000 ÂŁ per year.
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.
We are looking for an experienced Quantitative Research Engineer to work on our data and research platforms and partner closely with our quantitative researchers to enable and enhance their research productivity. In this role, you will apply your expertise in engineering and data science to develop essential and innovative tools, systems, and methodologies that streamline the research process, improve data analysis and simulation capabilities, and drive research efficiencies. This role requires a strong technical background, excellent problemâsolving skills, and the ability to work closely with crossâfunctional teams.
Key Responsibilities
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 largeâscale 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 crossâfunctional 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 thirdâparty 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
Skill Set and Qualifications
4+ years experience working in close partnership with quantitative researchers to develop, deploy and maintain quantitativelyâdriven 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
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 bestâinâclass 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 problemâsolving skills and the ability to design practical solutions to complex research challenges
Strong communication and collaboration skills to effectively work with crossâfunctional 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 wellâresourced startup environment, where your ideas, experience, and drive to find creative solutions makes a difference? We\âd 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.
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Quantitative Research Engineer employer: Numeus
Contact Detail:
Numeus Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Quantitative Research Engineer
â¨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Python, Dask, and NetworkX. Having hands-on experience with these will not only boost your confidence but also demonstrate your readiness to hit the ground running.
â¨Tip Number 2
Engage with the digital asset community by attending relevant meetups or webinars. This will help you network with professionals in the field and may even lead to insider information about the company culture and expectations at Numeus.
â¨Tip Number 3
Prepare to discuss your previous experiences in quantitative research and how you've collaborated with researchers. Be ready to share specific examples of how your technical solutions improved research productivity in past roles.
â¨Tip Number 4
Showcase your problem-solving skills by preparing a few case studies or scenarios where you successfully tackled complex challenges in data analysis or software development. This will highlight your ability to think critically and provide practical solutions.
We think you need these skills to ace Quantitative Research Engineer
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative research and software engineering. Emphasise your skills in Python, data processing, and any previous work with quantitative hedge funds.
Craft a Compelling Cover Letter: In your cover letter, express your passion for digital assets and how your background aligns with Numeus' values. Mention specific projects where you've collaborated with researchers to enhance productivity.
Showcase Technical Skills: Include specific examples of your technical expertise, such as your experience with tools like Dask or Ray, and your understanding of statistical modelling and machine learning techniques. This will demonstrate your capability to meet the job requirements.
Highlight Collaboration Experience: Since the role involves working closely with cross-functional teams, provide examples of past collaborations. Discuss how youâve successfully translated research requirements into technical solutions, showcasing your communication skills.
How to prepare for a job interview at Numeus
â¨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and any relevant tools like Dask or NetworkX. Highlight specific projects where you've built scalable systems or improved data analysis capabilities.
â¨Understand the Research Workflow
Familiarise yourself with the typical challenges faced by quantitative researchers. Be ready to suggest how your technical solutions can enhance their productivity and streamline their processes.
â¨Demonstrate Problem-Solving Abilities
Prepare examples of complex problems you've solved in previous roles, particularly those related to data processing or statistical modelling. This will show your ability to tackle challenges effectively.
â¨Emphasise Collaboration Skills
Since this role involves working closely with cross-functional teams, be sure to highlight your communication skills and any experience you have mentoring junior team members or collaborating on projects.