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- Tasks: Drive machine learning advancements and develop trading strategies in a dynamic environment.
- Company: Leading energy trading company in Greater London with a focus on innovation.
- Benefits: Competitive salary, health insurance, and extensive holiday leave.
- Why this job: Join a cutting-edge team and make a real impact in the trading world.
- Qualifications: 3+ years in machine learning, strong Python skills, and solid statistics knowledge.
- Other info: Collaborate with senior leaders and enhance trading capabilities.
The predicted salary is between 60000 - 80000 £ per year.
An energy trading company in Greater London is seeking a Quantitative Researcher to drive machine learning advancements in trading. You will work on developing trading strategies and indicators, collaborating with senior leaders to enhance trading capabilities.
Candidates should have:
- 3+ years in machine learning and software engineering
- Strong Python skills
- A solid understanding of statistics
This role offers a competitive salary and a range of employee benefits, including health insurance and extensive holiday leave.
ML Engineer - Quant Trading Platform & Time-Series in London employer: Dare
Contact Detail:
Dare Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer - Quant Trading Platform & Time-Series in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people 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 machine learning projects and trading strategies. This will give potential employers a taste of what you can bring to the table and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and statistics knowledge. Be ready to discuss your past experiences and how they relate to the role. Practice common interview questions to boost your confidence!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications that way!
We think you need these skills to ace ML Engineer - Quant Trading Platform & Time-Series in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning and software engineering. We want to see how your skills align with the role, so don’t be shy about showcasing your Python prowess and any relevant projects you've worked on.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about quantitative research and how you can contribute to our trading strategies. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Statistical Knowledge: Since a solid understanding of statistics is key for this role, make sure to mention any relevant coursework or projects. We appreciate candidates who can demonstrate their analytical skills and how they apply to trading.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Dare
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning concepts and algorithms. Be ready to discuss how you've applied these in real-world scenarios, especially in trading contexts. They’ll want to see your understanding of both theory and practical application.
✨Show Off Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot or explain your previous projects. Practise coding challenges related to data manipulation and algorithm implementation.
✨Statistics is Key
A solid grasp of statistics is crucial for this role. Brush up on statistical methods and be prepared to discuss how you’ve used them to inform trading strategies. They may ask you to interpret data or explain statistical models, so be ready!
✨Collaborate and Communicate
This role involves working closely with senior leaders, so highlight your teamwork and communication skills. Prepare examples of how you've successfully collaborated on projects in the past, especially in high-stakes environments like trading.