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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 chance to work with cutting-edge technology.
- Why this job: Be part of a team solving complex challenges while delivering high-quality returns for investors.
- Qualifications: Proficiency in Python, basic AWS knowledge, and a collaborative mindset are essential.
- Other info: Experience with data visualisation tools and advanced database skills 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’d 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
Quantitative Developer - Commodities- Systematic Quant Fund (London) employer: Placed
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 specific technologies mentioned in the job description, especially Python libraries like NumPy and Pandas. Consider working on personal projects or contributing to open-source projects that utilise these tools to showcase your skills.
✨Tip Number 2
Gain hands-on experience with AWS services relevant to the role, such as S3 and Lambda. You could set up a small project that involves deploying a cloud-based application to demonstrate your understanding of cloud architecture.
✨Tip Number 3
Network with professionals in the quantitative finance space, particularly those who work with commodities. Attend industry meetups or webinars to connect with potential colleagues and learn more about the latest trends and challenges in the field.
✨Tip Number 4
Prepare to discuss your collaborative experiences in team settings. Think of examples where you worked closely with others, especially in tech or data-driven projects, as this role emphasises a team player attitude.
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 requirements of the Quantitative Developer role. 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 where you developed ETL pipelines or worked with large datasets, demonstrating your fit for the role.
Showcase Technical Skills: In your application, clearly outline your technical skills, particularly 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 could be projects where you successfully worked with others to solve complex challenges.
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, pandas, and matplotlib. You might be asked to solve a coding problem or explain how you've used these tools in past projects.
✨Demonstrate Your Understanding of Cloud Technologies
Since the role involves working with AWS, brush up on your knowledge of cloud services. Be ready to talk about any previous experience you have with AWS, especially services like S3, Lambda, or DynamoDB.
✨Emphasise Collaboration and Teamwork
This position requires a collaborative mindset. Prepare examples of how you've worked effectively in teams, particularly in cross-functional settings involving researchers and engineers.
✨Prepare for Problem-Solving Questions
Expect questions that assess your quantitative mindset and problem-solving abilities. Think of scenarios where you've tackled complex challenges, especially those related to data integration or trading infrastructure.
