At a Glance
- Tasks: Apply cutting-edge Machine Learning techniques to financial forecasting and develop innovative trading strategies.
- Company: Join Cambridge Quantum Computing, a leader in quantum technology and machine learning.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative team atmosphere with a focus on research and innovation.
- Why this job: Make an impact in the finance sector using state-of-the-art ML and Deep Learning technologies.
- Qualifications: Master's degree in Machine Learning or related field; proficiency in Python and ML libraries.
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 in London 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 access to cutting-edge research opportunities, collaborative projects with experienced professionals, and a commitment to employee growth through continuous learning and development. The company fosters a dynamic environment where your contributions can directly impact the financial markets, making it a rewarding place for those passionate about machine learning and its applications.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Scientist in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the Machine Learning field on LinkedIn or at industry events. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and ML libraries. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on the latest ML research and techniques. Be ready to discuss how you've applied deep learning in real-world scenarios, especially in financial contexts.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes tracking your application super easy for us!
We think you need these skills to ace Machine Learning Scientist in London
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:Take a moment to customise your CV and cover letter for this role. We love seeing candidates who understand our needs and can demonstrate how their background aligns with the responsibilities of the Machine Learning Scientist position.
Research is Key:Stay updated with the latest trends in machine learning and deep learning. Mention any relevant research or projects you've worked on that relate to financial time-series forecasting, as this will 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 makes the process smoother for everyone involved!
How to prepare for a job interview at Cambridge Quantum
✨Know Your ML Stuff
Make sure you brush up on the latest trends and research in machine learning, especially deep learning. Be ready to discuss how these concepts apply to financial time-series forecasting, as this will show your passion and expertise in the field.
✨Showcase Your Coding Skills
Since proficiency in Python and its libraries is key, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice coding challenges that involve Numpy, Pandas, or TensorFlow to ensure you're sharp.
✨Prepare Real-World Examples
Think of specific projects where you've applied ML techniques, particularly in financial contexts. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will help you stand out as someone who can deliver practical solutions.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team’s current projects, their approach to deploying ML strategies, or how they stay updated with the latest research. This shows your genuine interest in the role and helps you gauge if it's the right fit for you.
