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Talent Acquisition Specialist at G-Research – Engineering
Do you want to tackle the biggest questions in finance with near infinite compute power at your fingertips?
G-Research is a leading quantitative research and technology firm, with offices in London and Dallas.
We are proud to employ some of the best people in their field and to nurture their talent in a dynamic, flexible and highly stimulating culture where world-beating ideas are cultivated and rewarded.
This role is based in our new Soho Place office – opened in 2023 – in the heart of Central London and home to our Research Lab.
The role
Engineering underpins our continued growth and success, and we are committed to recruiting and developing the world’s best Engineers.
Our Quantitative Developers are the enablers of our success. They work side-by-side with our researchers to realise their ideas in global financial markets. They work at the bleeding-edge with immense compute power at their fingertips to achieve our aim: predicting the future.
The core tech stack is C# and Python, productionised in our own datacentres.
Areas of focus for these teams include:
- Trading systems – reliable and performant systems able to trade 24/6 for our customers, with real money at stake
- Modelling – building core capabilities and assisting quant researchers in our cutting edge prediction capabilities
- Simulation – back-testing frameworks for validating the strategies our researchers produce and for assessing their ongoing performance
- Research tooling – front-end UX and workflow for our quant researchers
- Performance and scalability – optimising our trading and research systems to unlock new capabilities
To give a flavour of the work we do, here are some of our recent projects:
- Low level performance optimisations in our core simulation engine, unlocking the next advances in quant research
- Experimenting with alternative solvers in a core trade planning system
- Integrating our high and low frequency systems for more optimal trading
- Re-architecting systems to provide a seamless path from research to production for machine learning models
- Enabling large-scale distributed training of machine learning models
- Contributing back to open source projects
Who are we looking for?
The ideal candidate will have the following the skills and experience:
- Intelligent, pragmatic and capable engineers with a genuine interest in technology
- Proven ability to engineer high-quality software
- Appreciation of good architecture and engineering best practices
- End-to-end ownership of solutions: from articulation through to delivery
- Good understanding of fundamental algorithms and data structures
- An interest in the quantitative finance and an understanding of the role engineering plays within the space
- The ability to prioritise, plan and deliver to demonstrably drive business results
- The ability to proactively identify where we can improve and implement long term, scalable solutions to drive business outcomes.
- A proactive approach to learning, staying ahead of the technology curve and identifying how we can adopt new technologies in the ways we work
- Balanced judgement, with the ability to evaluate different approaches and identify solutions for the benefit of the overall business
- Adaptable communication styles and approaches tailored to their audience in order to convey compelling messages
- The ability to understand the needs and challenges of others and present mutually beneficial solutions
- A collaborative approach with the ability to build effective relationships across the business
Why should you apply?
- Highly competitive compensation plus annual discretionary bonus
- Lunch provided (via Just Eat for Business) and dedicated barista bar
- 35 days’ annual leave
- 9% company pension contributions
- Informal dress code and excellent work/life balance
- Comprehensive healthcare and life assurance
- Monthly company events
Seniority level
Seniority level
Not Applicable
Employment type
Employment type
Full-time
Job function
Job function
Information Technology, Engineering, and Finance
Industries
Financial Services and Capital Markets
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