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- Tasks: Design and develop core quantitative models and data systems from scratch.
- 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 who thrive in fast-paced, high-impact environments.
- Why this job: Join a small, elite team and make a direct impact on innovative solutions.
- Qualifications: Strong programming skills in Python and experience with quantitative or ML models.
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 such as Oxford, Cambridge, Imperial etc.
- 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
Asset Integrity Analysis Engineer in London employer: Cadogan Solutions
Contact Detail:
Cadogan Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Asset Integrity Analysis 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, data pipelines, or machine learning. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your programming skills and understanding 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 ready to make an impact. Your next big opportunity could be just a click away!
We think you need these skills to ace Asset Integrity Analysis 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 background aligns with the role, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements of the Asset Integrity Analysis Engineer position. Mention your experience with quantitative models and data systems, as this will catch our eye.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your achievements and experiences are easy to read and understand.
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!
How to prepare for a job interview at Cadogan Solutions
✨Know Your Quantitative Models
Make sure you brush up on your knowledge of quantitative models and how they drive product decisions. Be ready to discuss your past experiences in designing and implementing these models, as well as any challenges you've faced and how you overcame them.
✨Showcase Your Programming Skills
Since strong programming skills in Python and other languages like C++, Go, or Rust are crucial, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges beforehand to feel confident.
✨Understand Data Pipelines
Familiarise yourself with how models interact with data pipelines and infrastructure. Be prepared to discuss your experience in building and optimising large-scale data pipelines, and how you ensure scalability and reliability in low-latency environments.
✨Emphasise Your Ownership Mindset
In an early-stage startup, having a high ownership mindset is key. Share examples of how you've taken initiative in previous roles, especially in fast-paced environments, and how you contributed to the success of your team or project.