At a Glance
- Tasks: Drive innovative research in deep learning to transform financial markets.
- Company: Join Jump Trading Group, a leader in cutting-edge financial research.
- Benefits: Enjoy competitive salary, bonuses, health insurance, and generous leave policies.
- Other info: Dynamic team environment with opportunities for growth and innovation.
- Why this job: Make a real impact with your research while collaborating with top talents.
- Qualifications: 5+ years in deep learning, strong Python/C++ skills, and a relevant advanced degree.
The predicted salary is between 70000 - 90000 £ per year.
Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.
The quantitative trading teams at Jump Trading probe and examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis, machine learning and deep learning skills, using the results of their research to make forecasts and develop profitable predictive trading models.
What You’ll Do: We are seeking research scientists with a demonstrated ability to apply deep learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, statistics and market intuition. Other duties as assigned or needed.
Skills You’ll Need:
- 5+ years of experience in developing DL systems with measurable impact in industry and/or academia
- Creative thinkers who are driven, self-motivated, and eager to solve challenging problems
- Proficiency in Python and/or C++
- Strong foundation in mathematics and statistics
- Ability to thrive in a collaborative, team-oriented environment
- PhD, or Master's degree in Computer Science, Mathematics, (or related subject)
- Strong publications record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent
- Reliable and predictable availability
- Excellent written and verbal communication skills in English
Benefits:
- Discretionary bonus eligibility
- Medical, dental, and vision insurance
- HSA, FSA, and Dependent Care options
- Employer Paid Group Term Life and AD&D Insurance
- Voluntary Life & AD&D insurance
- Paid vacation plus paid holidays
- Retirement plan with employer match
- Paid parental leave
- Wellness Programs
Annual Base Salary Range $200,000 - $350,000 USD
Research Scientist/Research Engineer | Deep Learning in London employer: Jump Trading
Jump Trading is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for aspiring quantitative traders. With a focus on empowering talent through intensive training and mentorship, interns will gain hands-on experience in developing predictive models and automated trading strategies while working alongside industry experts. Located in a dynamic environment, Jump offers unique opportunities for personal and professional growth, ensuring that every team member can thrive and contribute to groundbreaking research in financial markets.
StudySmarter Expert Advice🤫
We think this is how you could land Research Scientist/Research Engineer | Deep Learning in 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 Jump Trading!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Research Scientist/Research Engineer | Deep Learning at Jump Trading.
✨Leverage Professional Networks
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 Jump Trading.
✨Apply Directly through Our Website
When you find a suitable opening like Research Scientist/Research Engineer | Deep Learning at Jump Trading, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Research Scientist/Research Engineer | Deep Learning 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!
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 Jump Trading, 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 Jump Trading. 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 Jump Trading
✨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 Jump Trading!
✨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.
