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Junior Data Scientist

Pozuelo de Alarcón, Madrid


This is for me
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This job is for you if...

You feel excited about applying Machine Learning techniques to the real world. You are logical, analytical, curious and creative. You know how to represent and analyse complex data structures in a simple and coherent way. Financial knowledge is a plus, but you're welcome if you don't have it, too: you'll learn here. You love Python programming.

What you'd have to do

  • Understand and evaluate the current investment methodology. (Don't panic, we'll teach you a couple of things...)
  • Apply Machine Learning techniques to improve the recommendation process.
  • Monitor and analyse portfolios.
  • Integrate developments and support in Python.

What we’d like to see

  • Someone recently graduated or currently finishing a Bsc/Msc in Maths, Physics, Engineering, Data Science or other related fields.
  • Knowledge of Machine Learning techniques.
  • Skilled at programming in Python.
  • Knowledge of data analysis.
  • High learning capacity.
  • Ability to work with others to achieve a specific goal together.

Nice to have

  • Strong communication skills.
  • Good English level (at least B2 or equivalent).

Here’s what you get

The opportunity to work in a Data Science team that handles leading-edge financial products and deals with complex scientific problems. You’ll make use of Machine Learning techniques to improve and develop real quantitative investment methodologies. You’ll be part of an autonomous team able to make its own decisions and responsible for delivering results. Fresh ideas are always welcome. You just got to persuade your team to turn them into reality.

You'll work for the leading Financial Advisor in Spain. You'll face big challenges and share an international environment where learning is permanently encouraged. Your colleagues will be pretty talented folks.

If you want to grow and be happy at the same time, this might be your place.

(We'll always keep you informed of where you stand in the application process).

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