At a Glance
- Tasks: Research and develop mathematical models for global trading opportunities.
- Company: Renowned trading business in Greater London with a collaborative culture.
- Benefits: Competitive salary, ownership opportunities, and impactful work.
- Other info: Dynamic environment with significant career growth potential.
- Why this job: Make a real impact in trading with your quantitative skills.
- Qualifications: PhD in a quantitative field and strong programming skills in Python or C++.
The predicted salary is between 60000 - 80000 £ per year.
Referment is seeking Quantitative Researchers for a distinguished trading business based in Greater London. This role involves researching and developing mathematical models to identify trading opportunities globally.
Successful candidates will have:
- A PhD in a quantitative field
- Strong programming skills in Python or C++
- A robust mathematical background
Join a collaborative environment with opportunities for significant ownership and impact.
Quantitative Researcher: ML-Driven Trading Signals (London) employer: Referment
Referment offers an exceptional work environment for Quantitative Researchers, fostering a culture of collaboration and innovation in the heart of Greater London. Employees benefit from significant ownership of their projects, ample opportunities for professional growth, and the chance to make a meaningful impact in the trading industry. With a focus on cutting-edge research and development, this company stands out as a rewarding place for those passionate about mathematics and technology.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Researcher: ML-Driven Trading Signals (London)
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Referment!
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Referment.
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We think you need these skills to ace Quantitative Researcher: ML-Driven Trading Signals (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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Referment, 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 Referment. 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 Referment
✨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!
✨Showcase Your Projects
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
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Referment!
✨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.
