At a Glance
- Tasks: Apply cutting-edge ML techniques to financial forecasting and develop innovative trading strategies.
- Company: Join a leading quantum computing firm with a focus on research and collaboration.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Work in a vibrant team with excellent career advancement opportunities.
- Why this job: Make an impact in finance using state-of-the-art machine learning technologies.
- Qualifications: Master's degree in ML or related field, proficiency in Python, and a passion for problem-solving.
The predicted salary is between 60000 - 80000 £ per year.
Cambridge Quantum Computing is looking to hire a Machine Learning Scientist for its Machine Learning unit. The role involves applying state-of-the-art Machine Learning and specifically, Deep Learning techniques to financial time-series forecasting on diverse sources of data. The successful candidate will join the London office and will be working in a highly dynamic, research-focused group, teaming up with senior members of the team and reporting directly to the project head.
Responsibilities
- Stay on par with the latest research literature in the ML field.
- Analyse high resolution financial data to identify statistically significant trading patterns and extract predictive features.
- Train state-of-the-art DL algorithms to learn profitable trading strategies.
- Prototype and implement new ML ideas in CQC’s proprietary R&D software platform.
- Deploy ML/DL strategies in the most competitive financial markets.
Key Requirements
- A master’s degree in Machine Learning or Computational Statistics from a top-tier University, or a degree in a quantitative discipline (Math, Physics, Computer Science) and relevant experience.
- Proficiency with Python 3 and its scientific/ML libraries such as Numpy, Pandas, Scikit-Learn, Tensorflow and Keras.
- Knowledge of Deep Learning fundamentals applied to a relevant domain (Computer Vision, Speech Recognition, Natural Language Processing etc.).
- A passion for approaching complex problems with the goal to design and deliver novel practical solutions.
Desirable Skills
- A PhD in relevant discipline and a track record of scientific publications.
- Hands-on experience in the development and deployment of ML systems gained in a commercial or research environment.
- Familiarity with time-series processing and feature extraction (particle filtering, state-space models, wavelet transforms, dimensionality reduction, etc.).
- Experience in collaborative software development and version-control systems (git).
All candidates must be eligible to live and work in the UK.
Machine Learning Scientist employer: Cambridge Quantum
Cambridge Quantum Computing is an exceptional employer, offering a vibrant and innovative work culture in the heart of London. As a Machine Learning Scientist, you will have the opportunity to collaborate with leading experts in the field, engage in cutting-edge research, and contribute to impactful projects that shape the future of financial technology. The company prioritises employee growth through continuous learning opportunities and fosters a supportive environment that encourages creativity and the pursuit of excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to Machine Learning and Deep Learning. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Machine Learning Scientist
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with Python and the ML libraries mentioned in the job description. We want to see how you've applied these skills in real-world scenarios, so don’t hold back!
Tailor Your Application:Customise your CV and cover letter to reflect the specific requirements of the Machine Learning Scientist role. We love seeing candidates who take the time to connect their experiences with what we’re looking for.
Research is Key:Stay updated on the latest trends and research in machine learning. Mentioning recent advancements or papers in your application can show us your passion and commitment to the field.
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Cambridge Quantum
✨Know Your Stuff
Make sure you brush up on the latest research in machine learning, especially deep learning techniques. Be ready to discuss how these can be applied to financial time-series forecasting, as this will show your passion and expertise in the field.
✨Showcase Your Skills
Prepare to demonstrate your proficiency with Python and its libraries like Numpy, Pandas, and Tensorflow. You might be asked to solve a problem on the spot, so practice coding challenges related to ML algorithms and data analysis beforehand.
✨Talk About Your Projects
Have a few examples of your past work ready to share, especially any projects involving ML systems or time-series data. Discuss the challenges you faced and how you overcame them, as this will highlight your problem-solving skills and practical experience.
✨Ask Smart Questions
Prepare thoughtful questions about the team’s current projects and the company’s approach to ML. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you.
