Offer description

  • Candidate Profile

    Design and engineer experiments on end to end scenarios. Build predictive models and conduct experiments to gain insights. Cross-collaborate with engineers on building statistical models, applying machine learning techniques for targeted solutions and effectively communicating the analysis and findings through interactive visualizations, documents and presentations. Assist our customers and our own projects with causal inferences and observations. Find patterns, relationships in data. The candidate will be incorporated into the Operations department within a multidisciplinary team and under an established professional career plan, working within data management, transformation, analysis, storage and visualisation projects.
  • Requirements

    • Experience in statistics, data mining and predictive modeling required
    • Experience using Statistical and Machine Learning algorithms on real data
    • PExcellent and wide ranging experience in supervised and unsupervised learning: Neural Networks, Bayes, Decision trees, Random forest , SVM, Clustering, Kmeans, PCA, Classifiers, deep learning…
    • Familiarity and experience with the standard machine learning packages, such as numpy, scipy scikit-learn, TensorFlow, keras and Theano
    • Experience in the use of the following languages: Python, PySpark, Spark, R
    • Candidate should be very client oriented, proactive, innovative, problem solver
    • Experience on Machine Learning tools over Google Cloud Platform, AWS and Microsoft Azure stack
    • English required

  • Benefits

    • Flexible hours
    • Up to 2 days of remote work per week, depending on the project
    • Team building activities: parties, meetups, talks, conferences, football team, rock band…
    • Training and certification plan
    • Career scheme and yearly salary reviews
    • 23+2 vacation days
    • Other benefits: Meal tickets, daycare vouchers, transportation, private health insurance for you and your family, spotify premium subscription

  • Location

  • Salary

    Based on experience and knowledge of the candidate