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Data Scientist - FinTech (26354)

Cambridge w/ hybrid working
£40k to £100k DoE
Filled

Developing forecasting and classification data models within finance

This Cambridge based group is a key engineering and data team for a multinational FinTech company. Their modern tech based products provide their customers the power and ease to easily track, send and receive money through intuitive interfaces. They are currently growing their Data Science team and seek a Data Scientist to join them.

Requirements

  • Top academics - likely 1st / high 2.1 degree in maths or physics from a top ranked (Russell Group or similar) university.
  • a PhD or relevant commercial experience with data science projects (graduates with extensive relevant internship experience will also be considered). The ability to design experiments and implement the right tools to extract meaningful analysis is needed.
  • Demonstrable experience with: Bayesian methods; analysis of large datasets; and relational databases (MySQL, PostGreSQL).
  • Exposure to ML tools for classification models or forecasting models would be useful.
  • Experience with Python and associated libraries would be desirable.

No specific finance knowledge is needed although an interest would be beneficial. Good communication skills are needed including being able to present technically-sophisticated models to a range of audiences. Hybrid working with occasional (depending on seniority and personal preferences) onsite meetings at their Cambridge offices is available.

In return, an excellent salary is on offer and the chance to work on new challenging projects.

Keywords: Grads / Masters / PhD / Experienced, Top Academics, Statistics, FinTech, Python, SQL, Bayesian Methods, Forecasting Models, Hybrid Working

Please note: even if you don't have exactly the background indicated, do contact us now if this type of job is of interest - we may well have similar opportunities that you would be suited to. And of course, we always get your permission before submitting your CV to a company.

Recommend for £250 - see www.ecmselection.co.uk/tell-a-friend for details.