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- Tasks: Design and implement cutting-edge quantitative models for data-driven systems.
- Company: Exciting early-stage startup at the forefront of machine learning and real-time environments.
- Benefits: Competitive salary, equity options, and a chance to shape the future of technology.
- Other info: Founding-level role with excellent growth opportunities in a dynamic startup environment.
- Why this job: Join a small, elite team and make a direct impact on innovative products.
- Qualifications: Strong background in Computer Science or related fields, with programming skills in Python and C++, Go, or Rust.
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
- 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 employer: Cadogan Solutions
Contact Detail:
Cadogan Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at startups or in quantitative roles. 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 quantitative models or data systems you've built. This is your chance to demonstrate your programming prowess in Python and other languages, making you stand out from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your statistics and programming skills. Practice coding challenges and be ready to discuss how you've tackled real-time data problems in the past. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Tailor your application to highlight your ownership mindset and experience in high-performance environments to catch our eye.
We think you need these skills to ace Quantitative Engineer
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming skills in Python and any experience with C++, Go, or Rust. We want to see how your background in Computer Science, Mathematics, or Statistics can contribute to our high-performance systems.
Be Specific About Your Experience: When detailing your past projects, focus on your experience with quantitative models and data pipelines. We love seeing concrete examples of how you've built and optimised systems, especially in real-time environments.
Demonstrate Your Ownership Mindset: Since we’re an early-stage startup, it’s crucial to show that you can take ownership of your work. Share instances where you’ve driven projects from concept to completion, and how you’ve thrived in dynamic environments.
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 get to know you better. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Cadogan Solutions
✨Know Your Quantitative Models
Make sure you can discuss your experience with quantitative models in detail. Be prepared to explain how you've designed and implemented them in the past, especially in high-performance environments. This will show your understanding of the core responsibilities of the role.
✨Showcase Your Programming Skills
Brush up on your Python skills and be ready to demonstrate your proficiency in at least one of C++, Go, or Rust. You might be asked to solve a coding problem during the interview, so practice common algorithms and data structures relevant to quantitative engineering.
✨Understand Data Pipelines
Familiarise yourself with how quantitative models interact with data pipelines and production systems. Be ready to discuss your experience in building and optimising data pipelines, as well as how you ensure scalability and reliability in low-latency environments.
✨Emphasise Your Ownership Mindset
Since this is an early-stage startup, they’ll want to see that you’re comfortable taking ownership of projects. Share examples of how you've taken initiative in previous roles, particularly in fast-paced or ambiguous situations, to demonstrate your fit for their team.