At a Glance
- Tasks: Build tools and infrastructure for the Commodities desk while implementing innovative models.
- Company: Tempest Vane Partners, a leading firm in the financial sector.
- Benefits: Competitive salary and opportunities for professional growth in a dynamic environment.
- Why this job: Join a forward-thinking team and shape the future of Commodities trading.
- Qualifications: Strong Python skills and experience in Commodities trading are essential.
The predicted salary is between 70000 - 90000 £ per year.
Tempest Vane Partners in London is seeking an experienced Quantitative Developer to join the Commodities desk. You will build tooling, infrastructure and implement models for the desk as it expands into new areas of the Commodities market. The role requires strong Python development experience and deep knowledge of Commodities trading, gained from a hedge fund, trading firm, or commodities team at an investment bank.
Senior Python Quant Developer - Commodities (London) employer: Tempest Vane Partners
At our London-based multi-strategy hedge fund, we pride ourselves on being a technology-first organisation that places data infrastructure at the heart of our investment strategies. We offer a dynamic work culture that fosters collaboration and innovation, providing engineers with significant opportunities for professional growth while working on cutting-edge cloud-native technologies and large-scale distributed systems. Join us to be part of a team that values intellectual curiosity and technical excellence in a fast-paced environment where your contributions directly impact our trading operations.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Python Quant Developer - Commodities (London)
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We think you need these skills to ace Senior Python Quant Developer - Commodities (London)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
