At a Glance
- Tasks: Lead research and develop models for funding decisions in a dynamic trading environment.
- Company: Hypernova, an innovative firm in Greater London focused on equity and trading risk.
- Benefits: Competitive salary, equity participation, and opportunities for professional growth.
- Other info: Be part of a fast-paced environment with significant impact on company success.
- Why this job: Join a pioneering team and shape the future of trading with your quantitative expertise.
- Qualifications: Strong background in quantitative analysis, risk management, and proficiency in Python.
The predicted salary is between 60000 - 80000 £ per year.
Hypernova in Greater London is seeking a Founding Quant Researcher to build and lead the research behind funding decisions. You will work with the trading team to develop essential models and manage exposure as the book grows.
The ideal candidate has a strong background in quantitative analysis and risk management, with proficiency in Python and trading systems.
The role offers a competitive salary range and meaningful equity participation in the company's success.
Founding Quant Researcher - Equity & Live Trading Risk employer: Hypernova
Hypernova is an exceptional employer located in the vibrant Greater London area, offering a dynamic work culture that fosters innovation and collaboration. As a Founding Quant Researcher, you will have unparalleled opportunities for professional growth and development, alongside competitive compensation and meaningful equity participation that aligns your success with the company's achievements. Join us to be part of a pioneering team where your contributions directly impact our trading strategies and overall success.
StudySmarter Expert Advice🤫
We think this is how you could land Founding Quant Researcher - Equity & Live Trading Risk
✨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 Hypernova!
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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 Hypernova.
✨Apply Directly through Our Website
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We think you need these skills to ace Founding Quant Researcher - Equity & Live Trading Risk
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 Hypernova, 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 Hypernova. 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 Hypernova
✨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 Hypernova!
✨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.
