At a Glance
- Tasks: Develop innovative tools and systems to enhance research productivity and data analysis.
- Company: Join a leading digital asset investment firm with a collaborative culture.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Make a real impact in a dynamic startup environment with cutting-edge technology.
- Qualifications: 4+ years in quantitative research, strong technical skills, and a relevant advanced degree.
- Other info: Opportunity to travel between offices in London, NYC, and Zug.
The predicted salary is between 54000 - 81000 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 problem‑solving skills, and the ability to work closely with cross‑functional 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 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.
- 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.
Quantitative Research Engineer employer: Numeus
Contact Detail:
Numeus Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Research Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Numeus or similar firms. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your projects related to quantitative research. This is your chance to demonstrate your technical prowess and problem-solving abilities.
✨Tip Number 3
Ace the interview by being ready to discuss real-world applications of your work. Think about how you've collaborated with teams before and be prepared to share specific examples that highlight your contributions.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Quantitative Research Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quantitative Research Engineer role. Highlight your experience with quantitative research, data analysis, and any relevant tools you've used. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about digital assets and how your background makes you a great fit for our team. Don't forget to mention any specific projects or achievements that showcase your expertise.
Showcase Your Technical Skills: Since this role requires a strong technical background, be sure to highlight your proficiency in programming languages, data processing tools, and any experience with machine learning. We love seeing concrete examples of how you've applied these skills in past roles.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you're keen on joining our team at Numeus!
How to prepare for a job interview at Numeus
✨Know Your Tech Inside Out
Make sure you brush up on your technical skills, especially in areas like Python, data processing, and machine learning. Be ready to discuss specific projects where you've applied these skills, as well as any challenges you faced and how you overcame them.
✨Understand Their Workflow
Familiarise yourself with the typical workflows of quantitative researchers. Think about how your engineering skills can enhance their productivity. Prepare examples of how you've collaborated with researchers in the past to solve problems or streamline processes.
✨Showcase Your Problem-Solving Skills
Be prepared to tackle some technical questions or case studies during the interview. Practice explaining your thought process clearly and logically, as this will demonstrate your problem-solving abilities and how you approach complex challenges.
✨Communicate and Collaborate
Highlight your experience working in cross-functional teams. Share examples of how you've effectively communicated technical concepts to non-technical stakeholders, as well as how you've mentored junior team members. This will show that you're not just a tech whiz but also a team player.