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- Tasks: Design and implement cutting-edge quantitative models for high-performance systems.
- Company: Early-stage startup at the forefront of machine learning and real-time data.
- Benefits: Strong compensation, meaningful equity, and a chance to shape the future.
- Other info: Join a small, elite team tackling complex quantitative challenges.
- Why this job: Be a founding engineer and make a direct impact on innovative products.
- Qualifications: Top-tier academic background in relevant fields and strong Python programming skills.
The predicted salary is between 60000 - 80000 £ per year.
Early-stage, well-funded startup building high-performance, data-driven systems at the intersection of machine learning and complex, real-time environments. You will be one of the first hires, owning the design and development of core quantitative models and data systems from the ground up.
What you’ll do:
- Design and implement quantitative models driving core product decisions
- Build and optimise large-scale data pipelines for model training and inference
- Work with real-time and batch data to improve prediction accuracy and system performance
- Partner closely with engineering to productionise models in low-latency environments
What they’re looking for:
- Strong academic background in Computer Science, Mathematics, Statistics, or a related field from a top-tier university
- Strong programming skills in Python and at least one of C++, Go, or Rust
- Strong appreciation of platform engineering: understands how models interact with data pipelines, infrastructure, and production systems; able to design with scalability, reliability, and latency constraints in mind
- Experience building and deploying quantitative or ML models in production
- Solid understanding of statistics, experimentation, and data-driven decision making
- Experience working with large-scale, real-time or high-frequency data
- High ownership mindset, comfortable operating in an early-stage environment
Nice to have:
- Experience in trading, optimisation, or ranking/recommendation systems
- Exposure to low-latency systems or performance-critical environments
- Background in startups or small, high-impact teams
Why join:
- Founding-level role with direct impact on product and technical direction
- Small, elite team solving complex quantitative problems
- Strong compensation and meaningful equity
Quantitative Engineer in London employer: Cadogan Solutions
Contact Detail:
Cadogan Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. The more you engage, the better your chances of landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, AWS, or any quantitative models you've built. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding of data pipelines. Practice common algorithms and data structures, and be ready to discuss how you've tackled real-time data challenges.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals who are ready to make an impact. Your next big opportunity could be just a click away!
We think you need these skills to ace Quantitative Engineer in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming skills in Python and any other languages you know, like C++, Go, or Rust. We want to see how your technical expertise aligns with the role, so don’t hold back!
Tailor Your Application: Customise your application to reflect the specific requirements of the Quantitative Engineer position. Mention your experience with quantitative models, data pipelines, and any relevant projects that showcase your ability to work in high-performance environments.
Be Authentic: Let your personality shine through! We’re looking for someone with a high ownership mindset who’s comfortable in an early-stage environment. Share your passion for the field and why you’re excited about this opportunity.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
How to prepare for a job interview at Cadogan Solutions
✨Know Your Quantitative Models
Make sure you brush up on your quantitative models and be ready to discuss how you've designed and implemented them in the past. Be prepared to explain your thought process and the impact your models had on product decisions.
✨Showcase Your Programming Skills
Since strong programming skills in Python and other languages are crucial, come prepared with examples of your coding work. You might even want to do a quick coding exercise during the interview, so practice common algorithms and data structures beforehand.
✨Understand Data Pipelines
Demonstrate your understanding of how models interact with data pipelines and infrastructure. Be ready to discuss any experience you have with building or optimising large-scale data systems, especially in low-latency environments.
✨Emphasise Your Ownership Mindset
As this is an early-stage startup, they’ll be looking for candidates who can take ownership of their work. Share examples of how you've taken initiative in previous roles and how you thrive in dynamic, fast-paced environments.