At a Glance
- Tasks: Design and develop high-frequency trading systems using C++ or Java.
- Company: Join a leading firm in quantitative finance with a focus on innovation.
- Benefits: Competitive salary plus benefits, with opportunities for professional growth.
- Other info: Gain hands-on experience in a dynamic environment with mentorship from industry experts.
- Why this job: Dive into the world of high-frequency trading and make your mark with your own strategies.
- Qualifications: PhD in a quantitative field and a passion for problem-solving.
The predicted salary is between 31500 - 38500 £ per year.
The group researches, defines, and optimizes high-frequency trading strategies that leverage cutting-edge technology to improve speed and market access to improve their trades. Working closely with an experienced Quant Strategist, you can utilize your quantitative, research, analytical, and programming skills to gather, house, and analyze data to help optimize existing models. As your experience grows, you will be expected to contribute your own strategy ideas. This is an excellent opportunity to learn about multiple asset classes and high-frequency trading whilst leveraging your current computational skills.
Responsibilities:
- Designing and developing systems built in C++ or Java
- Utilizing quantitative, research, analytical, and programming skills to gather, house and analyze data
- Contributing strategy ideas as experience grows
- Learning about multiple asset classes and high-frequency trading
Qualifications:
Candidates for this opportunity will have a PhD from a top tier University in Computer Science or other quantitative field such as Signal Processing, Data Mining, Mathematics, Operations Research etc. In addition to a stellar academic record, you will have a track record of professional quantitative or technology achievements. Ideally, you will have some research experience either in academia or in a research lab. Experience in the financial markets is a plus but not mandatory. A process-driven approach to problem-solving. Intellectual curiosity in quantitative finance.
Compensation: £ Base + benefits
Early Career Researcher in London employer: Eka Finance
As a leading player in the financial technology sector, our company offers an exceptional work environment in London, where innovation meets collaboration. We pride ourselves on fostering a culture of continuous learning and professional growth, providing employees with access to cutting-edge tools and technologies, as well as opportunities to work alongside industry experts. With competitive compensation and a commitment to work-life balance, we ensure that our team members thrive both personally and professionally while contributing to impactful quantitative research and trading solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Early Career Researcher in London
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We think you need these skills to ace Early Career Researcher in 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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Craft a Tailored Cover Letter:For a full-time role at Eka Finance, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Eka Finance. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Eka Finance
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
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.
