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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 environments.
- Benefits: Strong compensation, meaningful equity, and a chance to shape product direction.
- Other info: Ideal for those seeking ownership in a dynamic, fast-paced environment.
- Why this job: Join a small, elite team and make a direct impact on innovative solutions.
- Qualifications: Top-tier academic background in relevant fields and strong 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
Engineer, Risk Management in London employer: Cadogan Solutions
Contact Detail:
Cadogan Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Engineer, Risk Management in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at startups or in risk management. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on your dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, data pipelines, or machine learning models. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your programming skills and understanding of quantitative models. Practice coding challenges and be ready to discuss your thought process during problem-solving.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals who are passionate about building innovative solutions. Your next big opportunity could be just a click away!
We think you need these skills to ace Engineer, Risk Management 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 background aligns with the role, so don’t hold back!
Tailor Your Application: Customise your application to reflect the specific requirements of the Engineer, Risk Management position. Mention your experience with quantitative models and data systems, as well as any relevant projects you've worked on.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so make sure your achievements and experiences are easy to read and understand. Avoid jargon unless it’s necessary!
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’re considered for this exciting opportunity at our startup!
How to prepare for a job interview at Cadogan Solutions
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and any other programming languages mentioned, like C++, Go, or Rust. Be ready to discuss your past projects and how you've implemented quantitative models or data pipelines. They’ll want to see that you can not only code but also understand the underlying principles of what you're building.
✨Showcase Your Problem-Solving Skills
Prepare to tackle some real-time problem-solving scenarios during the interview. Think about how you would approach designing a quantitative model or optimising a data pipeline. Practise explaining your thought process clearly and logically, as they’ll be looking for your ability to think on your feet.
✨Demonstrate Your Ownership Mindset
Since this is an early-stage startup, they’ll value candidates who take initiative. Share examples from your past where you took ownership of a project or faced challenges head-on. Highlight your adaptability and willingness to dive into new areas, as this will resonate well with their team culture.
✨Understand Their Business and Market
Do your homework on the company’s focus areas, especially in high-frequency trading and machine learning. Familiarise yourself with current trends in crypto and equities. Being able to discuss how your skills align with their goals will show that you’re genuinely interested and invested in their mission.