At a Glance
- Tasks: Uncover market patterns and validate hypotheses using data.
- Company: Join QST Financial, a leading prop trading firm since 2008.
- Benefits: Competitive salary plus bonuses, relocation support, and cutting-edge tech resources.
- Other info: Dynamic team environment with opportunities for growth and relocation to Limassol.
- Why this job: Make an impact in finance with your research skills and innovative ideas.
- Qualifications: Strong maths background, Python proficiency, and ML experience required.
The predicted salary is between 40500 - 49500 £ per year.
Brief description of the vacancy: We are looking for a researcher with a strong mathematical background, confident in Python and practical experience in ML, who can independently conduct research from idea to result. We also consider strong graduates with notable achievements - Olympiads, ICPC, Codeforces, Kaggle, experience in HFT. Location: Limassol (on-site, relocation) or hybrid in Moscow.
About The Company: QST Financial is a proprietary trading company that has been trading its own capital since 2008. The team consists of 35 people, with an average experience of over 6 years. They trade derivatives (futures and options) on major exchanges such as CME, Eurex, NSE, KRX, etc. Trading volume exceeds $80B per month.
Responsibilities:
- Identify potential market patterns
- Formulate and test hypotheses on data
- Check results for stability, exclude data leakage and overfitting
- Bring working ideas to launch together with developers
Requirements:
- Strong mathematics, probability theory, and statistics
- Confident in Python
- Practical experience with ML
- Experience working with large datasets, understanding of model validation
- Ability to critically evaluate own results
- Independence and high research culture
- Final year or completed education in mathematics/physics/CS and related fields
- Ability to effectively use AI tools in research work
Will be a plus:
- Prize places in international Olympiads (mathematics, computer science, programming, physics)
- ICPC, Codeforces 2800+
- High results on Kaggle / competitive data science
- PhD, publications, serious academic work
- Experience in algorithmic trading / HFT
- Experience in independently bringing research ideas to production
Working conditions:
- Fixed salary + bonus / profit share
- The entire process from hypothesis to launch in real trading is structured within the company: own platform, FPGA and GPU cluster for heavy models
- On-site: relocation to Limassol (the company assists with visa and relocation) or hybrid in Moscow.
Quantitative Researcher in Moscow employer: ODS Serbia
QST Financial is an exceptional employer for Quantitative Researchers, offering a dynamic work environment in Limassol or a hybrid model in Moscow. With a strong focus on employee growth and a collaborative culture, the company supports research from hypothesis to real trading, providing access to advanced technology like FPGA and GPU clusters. Employees benefit from competitive compensation, including bonuses and profit sharing, while being part of a tight-knit team with extensive experience in the field.
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We think this is how you could land Quantitative Researcher in Moscow
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We think you need these skills to ace Quantitative Researcher in Moscow
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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✨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.
