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- Tasks: Develop ETL pipelines and manage cloud systems for large datasets in commodities trading.
- Company: Join a global leader in quantitative investment, driven by data and technology.
- Benefits: Enjoy a culture of innovation, collaboration, and the potential for high-quality returns.
- Why this job: Be part of a team solving complex challenges with cutting-edge technology and research.
- Qualifications: Proficiency in Python, basic AWS knowledge, and a collaborative mindset are essential.
- Other info: Experience with data visualisation tools and geographic data is a plus.
The predicted salary is between 43200 - 72000 £ per year.
My client is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. A technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped the collaborative mindset, enabling them to solve the most complex challenges. They have a culture of innovation which continuously drives their ambition to deliver high quality returns for investors.
The role:
- Develop ETL pipelines to integrate and test very large alternative datasets for the Commodities desk in collaboration with quant researchers and data engineering teams.
- Architect, deploy and manage cloud-based systems for storing and exploring very large alternative datasets in collaboration with the AWS infrastructure team.
- Monitor, support, debug and extend existing Commodities trading and research infrastructure together with Researchers and Support Engineers.
Requirements:
- Comfortable in Python, in particular numerical libraries - numpy, pandas, matplotlib, etc.
- Basic knowledge of AWS.
- Basic knowledge of databases (e.g. SQL).
- Development practices - version control with Git, unit testing, etc.
- A quantitative mindset.
- Team player and collaborative attitude.
Nice to have:
- Experience creating dashboards or using data visualization software (e.g. Tableau, Dash).
- In-depth AWS experience (e.g. DynamoDB, RDS, S3, Lambda, AWS CDK).
- Advanced database knowledge (query optimisation, relational vs non-relational databases, etc.).
- Parallel computation.
- Experience with geographic data using geopandas, xarray.
- Financial knowledge is a plus but not required.
Contact: If this sounds like you, or you would like more information, please get in touch: George Hutchinson-Binks, george.hutchinson-binks@oxfordknight.co.uk, (+44) 07885 545220, linkedin.com/in/george-hutchinson-binks-a62a69252
Contact Detail:
Placed Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Developer - Commodities- Systematic Quant Fund (London)
✨Tip Number 1
Familiarise yourself with the latest trends in quantitative finance and commodities trading. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the industry, especially those working in quantitative roles or at systematic funds. Attend relevant meetups or webinars to build connections that could lead to referrals.
✨Tip Number 3
Brush up on your Python skills, particularly with libraries like numpy and pandas. Consider working on personal projects or contributing to open-source projects to demonstrate your coding abilities.
✨Tip Number 4
Gain hands-on experience with AWS services relevant to the role. You can do this by setting up your own cloud-based projects or completing online courses that focus on AWS for data management.
We think you need these skills to ace Quantitative Developer - Commodities- Systematic Quant Fund (London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the job description. Emphasise your proficiency in Python, AWS, and any experience with data visualisation tools.
Craft a Compelling Cover Letter: Write a cover letter that showcases your quantitative mindset and collaborative attitude. Mention specific projects or experiences that demonstrate your ability to work with large datasets and cloud-based systems.
Showcase Technical Skills: In your application, clearly outline your technical skills, especially in Python libraries like numpy and pandas, as well as your knowledge of databases and version control practices. This will help you stand out to the hiring team.
Highlight Team Collaboration: Since the role requires collaboration with quant researchers and data engineering teams, include examples of past teamwork experiences. This can illustrate your ability to work effectively in a team-oriented environment.
How to prepare for a job interview at Placed
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and its numerical libraries like numpy and pandas. You might be asked to solve a problem on the spot, so brush up on your coding skills and be ready to demonstrate your knowledge.
✨Understand the Role of Cloud Computing
Since the role involves working with AWS, make sure you have a basic understanding of cloud services. Familiarise yourself with key AWS components like S3 and Lambda, and be ready to discuss how you've used them in past projects.
✨Emphasise Collaboration
This position requires a team player attitude. Be ready to share examples of how you've successfully collaborated with others, particularly in a tech-driven environment. Highlight any experiences where you worked closely with researchers or engineers.
✨Prepare for Problem-Solving Questions
Expect questions that assess your quantitative mindset and problem-solving abilities. Think of scenarios where you've had to analyse complex data sets or troubleshoot issues, and be ready to explain your thought process clearly.
