At a Glance
- Tasks: Apply machine learning and statistical methods to financial data and build production ML systems.
- Company: Join Dex, a leading firm in the financial tech space.
- Benefits: Earn up to £500,000+ with competitive compensation and growth opportunities.
- Other info: Work in a dynamic office environment five days a week.
- Why this job: Make an impact in finance using cutting-edge machine learning techniques.
- Qualifications: Strong background in quantitative research, Python, and SQL skills required.
Dex is seeking a ML / Quant Research Engineer in London, working five days a week in-office. You will apply machine learning and statistical methods to financial data, including building and deploying production ML systems.
Ideal candidates have a strong background in quantitative research, statistical fundamentals, and proficiency in Python and SQL.
The position offers a total compensation of up to £500,000+.
ML/Quant Research Engineer — Production Systems (London) employer: Dex
At Dex, we pride ourselves on fostering a dynamic and innovative work culture that empowers our employees to excel in their roles. As a ML/Quant Research Engineer in London, you will benefit from competitive compensation, opportunities for professional growth, and a collaborative environment that encourages the application of cutting-edge machine learning techniques to real-world financial challenges.
StudySmarter Expert Advice🤫
We think this is how you could land ML/Quant Research Engineer — Production Systems (London)
✨Tip Number 1
Network like a pro! Reach out to folks 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 machine learning projects, especially those involving financial data. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and SQL skills. Practice coding challenges and be ready to discuss your quantitative research experience in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace ML/Quant Research Engineer — Production Systems (London)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning and quantitative research. We want to see how your skills in Python and SQL can shine through, so don’t hold back on those relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for the ML/Quant Research Engineer role. Share your passion for financial data and any unique insights you have about deploying production ML systems.
Showcase Your Projects:If you've worked on any interesting projects related to machine learning or statistical methods, make sure to include them! We love seeing practical applications of your skills, especially if they relate to finance.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Dex
✨Know Your ML Fundamentals
Brush up on your machine learning and statistical methods. Be ready to discuss how you've applied these concepts in past projects, especially in financial contexts. This will show that you not only understand the theory but can also implement it effectively.
✨Showcase Your Coding Skills
Since proficiency in Python and SQL is crucial, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice common algorithms and data manipulation tasks beforehand. Make sure you can explain your thought process clearly.
✨Prepare for Real-World Scenarios
Expect questions that relate to building and deploying production ML systems. Think of examples from your experience where you faced challenges in deployment and how you overcame them. This will highlight your practical knowledge and problem-solving skills.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's approach to ML and quantitative research. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals.
