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Principal Data Scientist

Location:
Lisbon
Salary:
€60000 - €80000 per annum + benefits
Job Type:
Permanent
Date Posted:
19 days ago
Expiry Date:
28/06/2024
Job Ref:
BBBH110084_1716992285
Start Date:
29/05/2024
Contact:
Niall Wharton
Contact Email:
niall.wharton@xcede.com
Specialism:
Data ScienceAI & Machine LearningMachine LearningData

PRINCIPAL DATA SCIENTIST

Xcede are delighted to be working with one of the world's largest gaming companies on the scale-up of their pre-existing Data Science & Machine Learning Division. The organisation have an enviable wealth of digital / B2C data available to them given the scale of their userbase. The company would like to capitalise further on this, hence their ambitious (but well-defined) hiring plans.

The company is looking to hire experienced Data Scientists at a couple of different levels - Data Scientist / Senior Data Scientist / Principal Data Scientist. Projects will focus on Recommender Systems / Recommendation Engines, Customer Personalisation, etc.

The company have already made some heavyweight appointments, with the ML Leadership team coming from a number of FAANG organisations. This is a fantastic environment to improve your skillset and encounter new ideas.

Requirements

  • An academic background in Statistics, Mathematics, or Computer Science (or similar)
  • A number of years of commercial experience as a data scientist appropriate to your grade.
  • Commercial experience in designing impactful machine learning models
  • Experience in helping to take said models to production / deployment
  • Python expertise proven by writing production quality code

Bonus Requirements

  • System / Recommender System / Recommendation Engine / RecSys experience
  • PySpark experience
  • Azure DataBricks experience

If this role interests you and you would like to find out more, please apply here or contact us via niall.wharton@Xcede.com (feel free to include a CV for review).

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Niall Wharton

Niall Wharton

Specialisms: Data, Data Engineering, AI & Machine Learning, AI Research, NLP, Machine Learning, Computer Vision, Generative AI, AI Engineering
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