G-Research is a leading quantitative research and technology company. By using the latest scientific techniques, we produce world-beating predictive research and build advanced technology to analyse the world’s data.
Software Engineering is core to our business. By designing and implementing real-time systems, our engineers are solving some of the world’s most complex financial problems.
Our business is to predict the future of financial markets, applying scientific techniques to find patterns in large, noisy, and rapidly changing datasets. Every new dataset has the potential to yield new research initiatives, and our mission as a team is to maximise the number of useful datasets that quants can analyse.
In this role, you will apply your data engineering expertise to help build a next generation data ingestion and transformation platform to support the companies growing data requirements. You will be building a platform that will allow a scale up in the data science team’s ability to process data and deliver a significant advancement in the firm’s data productivity. You will be hands on with big data and NoSQL technologies and will be building microservices and tooling that facilitate the ability to ingest new datasets. You will be working hand in hand with data scientists to understand their requirements and translate these into enterprise scale solutions.
This is an exciting new role that will offer exposure to cutting-edge technologies in a high growth industry, with opportunities to learn about multi-asset class systematic investing and big data development in an innovative and forward-thinking firm. It will give an opportunity to make a big impact in a critical part of a growing business. You will be working with cutting edge technologies in an ambitious and technically focussed firm.
Who are we looking for?
You will be an intelligent, capable and hands-on engineer who is enthusiastic and has a genuine interest in both software technology and data science. You will have proven ability to engineer high quality software and experience with python and pandas in a data science context.
The successful candidate will have:
Why should you apply?