Quantitative Analyst – Data Informatics
Imagine discovering something undiscovered
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.
We use the latest scientific techniques and advanced data analysis methods to discover the undiscovered. Our researchers are free to explore ideas, finding patterns in large, noisy and real-world data sets to predict the movements in global financial markets.
We are looking to extract and analyse big datasets to identify anomalous, inefficient or advantageous behaviour internal to the platform or externally in the market. Our Data Informatics team works with Quantitative Research and Software Engineering teams across the business to discover these new performance enhancing opportunities.
As an analyst in the Quant Ops – Data Informatics team you will be responsible for using different methods of extracting and analysing big datasets to identify anomalous, inefficient or advantageous behaviour internal to the platform or externally in the market. These investigations can be driven by designing targeted metrics or by following up on a hypothesis ad-hoc.
You will monitor a myriad of inputs into the platform and ensure changes to these do not cause significant regression in performance. There will also be an element of validating new signals, releases and platform changes to ensure performance is aligned to expected changes and slippage is minimal. You must understand the limitations of the platform and therefore the true maximum potential. Where necessary you will need to engineer your own data solutions.
What are we looking for?
The ideal candidate will at minimum have experience in the following areas:
- 2:1 degree in a technical discipline
- Be experienced in Python (both for data science and app building)
- Fluent in SQL
- Experience working with HDFS infrastructure (Spark/Scala) is beneficial
- You should be interested in financial markets, as well as data science and visualisation methods
Why should you apply?
- Highly competitive compensation plus annual discretionary bonus
- Informal dress code and excellent work/life balance
- Comprehensive healthcare and life assurance
- 25 days holiday
- Contributory pension scheme
- Monthly company events
- Central London office close to 5 stations and 6 tube lines