Data Scientist – 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 work with the Quantitative Research and Software Engineering teams across the business to discover new performance enhancing opportunities through insights from internal and external sources. We productionise and improve methods of detecting and predicting outliers stemming from black box processes, most frequently represented in time-series form.
As a Data Scientist in the Quant Ops – Data Informatics team you will be responsible for seeking out these performance enhancing opportunities. You must understand the myriad of inputs into the platform and the predicted consequences in calibrating your models to ensure and accurately informed results. These results will be used to implement sensible changes to real-time platforms, as well as providing feedback to Quant and Engineering teams and indicating direction for further projects.
You will design models to analyse black box datasets for inefficiencies or opportunities. You will look to gain a solid understanding of behaviour, limitations of the platform and therefore its maximum potential Communicating and visualising hypotheses and conclusions concisely and clearly to research, business and development teams will also be a key part of your role.
Who are we looking for?
The ideal candidate will at minimum have experience in the following areas:
- 2:1 degree in a technical discipline
- Proficient in Python (both for data science and app building)
- Fluent in SQL
- Building and productionising ML models
- Approaching and analysing big data sets.
- 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