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- Tasks: Develop cutting-edge trading models using machine learning and Python.
- Company: Dynamic tech firm specialising in sports analytics.
- Benefits: Performance-based bonus, private healthcare, and gym membership.
- Why this job: Join a team that shapes the future of trading with innovative technology.
- Qualifications: Quantitative degree and strong software engineering skills.
- Other info: Collaborative environment with opportunities for personal and professional growth.
The predicted salary is between 60000 - 80000 £ per year.
A technology firm specializing in sports analytics is seeking a Machine Learning Engineer to develop production-ready trading models. You will work closely with quantitative researchers to build Python-based tooling and frameworks that enhance strategy research and minimize latency in trading operations.
The ideal candidate holds a quantitative degree and possesses significant software engineering skills.
Benefits include:
- a performance-based bonus
- private healthcare
- gym membership
Senior ML Engineer — Production‑Ready Trading Models in London employer: Longshot Systems
Contact Detail:
Longshot Systems Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer — Production‑Ready Trading Models in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in sports analytics or trading. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those related to machine learning and trading models. This will give you an edge when discussing your experience with potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding of algorithms. Practice common ML problems and be ready to discuss your thought process during the interview.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting roles, and applying directly can sometimes give you a better chance of landing that dream job.
We think you need these skills to ace Senior ML Engineer — Production‑Ready Trading Models in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and any relevant machine learning projects. We want to see how your skills align with the role, so don’t be shy about showcasing your quantitative degree and software engineering prowess!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about sports analytics and how your background makes you the perfect fit for developing trading models. Let us know what excites you about this opportunity!
Showcase Your Projects: If you've worked on any production-ready models or relevant tooling, make sure to mention them in your application. We love seeing real-world applications of your skills, so include links to your GitHub or any other portfolio that showcases your work.
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. Plus, it shows us you’re keen to join the StudySmarter team!
How to prepare for a job interview at Longshot Systems
✨Know Your ML Models Inside Out
Make sure you can discuss various machine learning models and their applications in trading. Be prepared to explain how you've implemented these models in past projects, focusing on the production-ready aspect.
✨Brush Up on Python Skills
Since the role involves building Python-based tooling, ensure you're comfortable with Python programming. Practice coding challenges that relate to data manipulation and algorithm implementation to showcase your software engineering skills.
✨Understand the Trading Landscape
Familiarise yourself with the basics of trading and sports analytics. Being able to discuss how your work can impact trading strategies will show your potential employer that you understand the business side of things.
✨Prepare Questions for Them
Think of insightful questions to ask during the interview. This could be about their current projects, team dynamics, or how they measure success in their trading models. It shows you're genuinely interested and engaged.