Data Scientist – Data Informatics
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.
Engage with Quantitative Research and Software Engineering teams across the business to discover new performance enhancing opportunities through insights from internal and external sources
As a data scientist in the Data Informatics team your key role will be to productionise and improve methods of detecting and predicting outliers stemming from black box processes, most commonly multivariate time-series datasets. Understanding the myriad of inputs into the platform and the predicted consequences is crucial in calibrating your models to ensure an accurately informed result. These results will be used to implement sensible changes to real-time platforms, as well as providing feedback to other Quant and Engineering teams and generating business insight to direct further projects.
You will be expected to leverage your knowledge to advise others on what methods may be best suited to projects taking off, and be comfortable with communicating complex ideas and solutions to a range of technical minds. There will be an element of visualising and communicating the final results both to research and business partners. Key responsibilities include:
- Design models to analyse black box datasets for inefficiencies or opportunities
- Investigate said behaviour through to conclusion using investigative techniques/models to glean a better understanding of the behaviour and how to improve the platform as a result
- Communicate and visualise hypotheses and conclusions concisely and clearly to research, business and development teams
- Engineering your own data solutions where necessary
- Design and improve anomaly detection models across the many data sources – primarily stochastic time-series
What are we looking for?
The ideal candidate will at minimum have experience in the following areas:
- Minimum Bachelor’s degree in quantitative, STEM or other technical discipline
- 2+ years of experience in an applied data analysis role
- Confident approaching large and complex datasets and applying various statistical methods (clustering, distribution analysis, dimension reduction) – preferably in Python
- Experience with visualisation technology to represent complex datasets and relationships (Such as Tableau, Matplotlib etc.)
- Demonstrated problem solving ability
The following are not required but are beneficial:
- Exposure to financial markets
- Experience in developing and applying multi-variate time series models
- Functional knowledge of SQL
- Applied machine learning to production datasets
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
- Monthly company events
- Central London office close to 5 stations and 6 tube lines
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