At a Glance
- Tasks: Tackle complex software challenges in automated trading and develop innovative solutions.
- Company: Leading algorithmic trading firm in London with a focus on cutting-edge technology.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Join a dynamic team solving real-world problems at the intersection of finance and technology.
- Qualifications: Experience in software engineering and a strong mathematical background.
The predicted salary is between 70000 - 90000 £ per year.
When you think about being challenged by a set of interesting problems in software engineering, what do those typically look like? We're working with a team of engineers at an algorithmic trading firm in London, which solves problems that sit at an incredibly interesting intersection: financial instruments, game theory and distributed systems.
Why is their work interesting?
- Latency. They write code where the execution path is profiled in microseconds because they're racing other teams to the same opportunity.
- Profit discovery. Finding an edge in automated trading means they've built their own data infrastructure. This indexes on-chain state, reconstructs order books from venues, tracks wallet behavior across chains. Their pipelines process millions of events and make them queryable in milliseconds.
- Probabilistic trading models. When they submit a trade, they don't know if it lands, when it lands, or what state the world is in when it does. The code's logic has to reason about: what if this reverts? What if gas spikes and I'm outbid? What if the price moves between simulation and inclusion? The code they write simulates the full execution against a forked state before committing.
- Heavily math oriented. Their work solves for optimal trade size across venues with non-linear price impact, factoring execution costs at execution time. This may look like implementing constant product formula, concentrated liquidity tick math and Curve stableswap invariants directly in their simulation layer so they can price routes without hitting an RPC.
- Signal to noise analysis. Where they trade, the data is public and permanent, which sounds great until you realize everyone has the same data. Their edge is in how fast it's processed, reconstructed and opportunities identified before they get arbed away. This means they end up writing a lot of heuristics for classifying transactions.
Who they need to join them? There are two avenues they are prioritising:
- Software Engineer with several years of experience from a tech-driven company, supported by top-class academics. Existing team members hold IMO/IOI medals.
- Software Engineer from the world of proprietary trading, who may have experimented with on-chain trading strategies before.
Senior Software Engineer employer: QNT Partners
Join a leading algorithmic trading firm in London, where you'll be immersed in a dynamic work culture that thrives on innovation and collaboration. With a focus on cutting-edge technology and complex problem-solving, we offer exceptional growth opportunities for our engineers, supported by a team of top-tier professionals. Enjoy the unique advantage of working at the heart of the financial district, where your contributions directly impact our success in the fast-paced world of automated trading.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Software Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, conferences, or even online webinars related to automated trading and software engineering. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your projects, especially those that involve financial instruments or distributed systems. Share it on platforms like GitHub and make sure to link it in your applications. We love seeing what you can do!
✨Tip Number 3
Prepare for technical interviews by brushing up on your algorithms and data structures. Practice coding challenges that focus on latency-sensitive applications. Remember, they want to see how you think under pressure, so simulate real interview conditions!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate candidates who are ready to tackle interesting problems in software engineering.
We think you need these skills to ace Senior Software Engineer
Some tips for your application 🫡
Show Your Passion for Problem-Solving:When you’re writing your application, let us see your enthusiasm for tackling complex problems. Share examples of challenges you've faced in software engineering, especially those that relate to financial instruments or distributed systems. We love seeing how you think through tough situations!
Highlight Relevant Experience:Make sure to emphasise your experience in tech-driven environments or proprietary trading. If you've worked on projects involving automated trading or have a background in game theory, shout about it! We want to know how your skills align with the interesting work we do.
Be Clear and Concise:We appreciate clarity in applications. Keep your language straightforward and avoid jargon unless it's relevant. Remember, we’re looking for engineers who can communicate complex ideas simply, so show us you can do just that in your written application!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at QNT Partners
✨Know Your Algorithms
Brush up on your algorithms and data structures, especially those relevant to trading systems. Be prepared to discuss how you’ve implemented them in past projects, as this will show your technical depth and problem-solving skills.
✨Understand the Financial Landscape
Familiarise yourself with financial instruments and trading strategies. Being able to speak knowledgeably about market dynamics and how they relate to automated trading will impress your interviewers and demonstrate your genuine interest in the role.
✨Prepare for Technical Challenges
Expect to tackle some coding challenges during the interview. Practice coding under time constraints and focus on optimising for latency and efficiency, as these are crucial in algorithmic trading environments.
✨Showcase Your Mathematical Skills
Since the role is heavily math-oriented, be ready to discuss your experience with probabilistic models and any relevant mathematical concepts. Highlight any projects where you’ve applied these skills, particularly in a trading context.
