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Data Scientist – Data Intelligence

Quantitative Research

Data Scientist – Data Intelligence

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.

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.

The role

In this role, you will apply your knowledge to support the exploration, enrichment and even creation of new datasets for research. You will use your knowledge of data blending, statistical analysis, and machine learning methods to help scale and automate the way we analyse, validate and visualise diverse data sources; and you will help build tooling to enable data science initiatives across the company.

This is a team at the forefront of the company’s data strategy, responsible for finding solutions to some of the many important data challenges within the firm, meaning you will have a unique opportunity to make an impact from the beginning. The successful candidate will be comfortable working within a multi-disciplinary team, collaborating with industry leading data scientists and financial experts, developing solutions that adapt to a rapidly changing data landscape.

The role will offer exposure to cutting-edge technologies in a high growth industry, with opportunities to learn about multi-asset class systematic trading ideas and big data development in an innovative and forward-thinking firm.

Who are we looking for?

The ideal candidate will at minimum have experience in the following areas:

  • Strong degree in numerical subject (Machine Learning, NLP, Mathematics, Data Science, Computer Science, Statistics, Physics, Engineering, etc.)
  • Advanced knowledge of Python, in particular packages such as Pandas, Numpy, SciPy, Matplotlib (or equivalent). Knowledge of PySpark/Scala is a bonus
  • Practical understanding of SQL and NoSQL databases
  • Experience selecting, developing and refining machine-learning models
  • Knowledge and/or interest in Natural Language Processing
  • Demonstrable proficiency in statistical data analysis and data visualisation
  • Confidence to build relationships with both internal teams and external vendors, and ability to communicate effectively with both technical and non-technical audiences
  • Previous financial experience is not required, although an interest in financial markets and securities is desirable
  • Contributions to Open Source repositories/competitions (e.g. GitHub, Kaggle)

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
  • Cycle-to-work scheme
  • Subsidised gym membership
  • Monthly company events
  • Central London office close to 5 stations and 6 tube lines
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