At a Glance
- Tasks: Lead innovative deep learning projects and collaborate with top-tier teams.
- Company: Jump Trading Group, a leader in quantitative research and monetization.
- Benefits: Competitive salary, cutting-edge resources, and opportunities for professional growth.
- Other info: Join a dynamic team focused on reliability and innovation in financial markets.
- Why this job: Make a real impact in finance using advanced deep learning techniques.
- Qualifications: 5+ years of deep learning experience, PhD/MSc in CS/Math, and strong coding skills.
The predicted salary is between 60000 - 80000 £ per year.
Jump Trading Group in Greater London seeks a research scientist to apply deep learning to state-of-the-art problems across quantitative research and monetization.
You will lead open-ended projects from concept to production, collaborating with ML, statistics, and engineering teams.
The role requires 5+ years of DL experience, a Ph D or MSc in CS/Math, Python and/or C++, and a strong publication record; you will contribute to cutting-edge models and tools with a focus on reliability and impact.
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Senior Research Scientist - Deep Learning for Markets in London employer: P2P
P2P is an exceptional employer that fosters a dynamic work culture focused on innovation and collaboration in the heart of Greater London. With a commitment to employee growth, we offer extensive professional development opportunities and a supportive environment for those passionate about advancing decentralized finance. Join us to be part of a forward-thinking team that values your contributions and encourages meaningful impact in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Research Scientist - Deep Learning for Markets in London
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We think you need these skills to ace Senior Research Scientist - Deep Learning for Markets 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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✨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 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.
