.GFT is a business change and IT company trusted by the world's leading financial institutions to meet the demands of the digital revolution. Innovation and creativity are part of our DNA and drive our own success story.Your main responsibilities:Implement complete data science pipelines to solve business problems, including data extraction, data preprocessing, exploratory data analysis, feature engineering, machine/deep learning modeling, and application deployment.Extraction and selection of features, building and optimizing supervised models using machine/deep learning.Processing, cleansing and verifying data integrity used for the analysis processes.Automate data science processes and ml-systems and constant tracking of its performance.Research and analyze state-of-the-art machine learning techniques.Write technical documentation and results.Company:GFT GroupQualifications:Minimum requirements:Passion and enthusiasm for data science and machine learning.3+ years of experience researching and/or developing applications in Python.2+ years of experience solving data science problems in Python (Scikit-learn, TensorFlow, Keras, Pytorch, Pandas, Numpy, MatplotLib).Demonstrable experience implementing supervised models using machine/deep learning techniques, including word embeddings, convolutional and recurrent neural networks, and gradient boosting.Knowledge and experience processing structured and unstructured data, especially Natural Language Processing (text extraction, text-based feature engineering, ...).Solid understanding of machine/deep learning concepts like backpropagation, gradient descent, vanishing gradient problem, data leakage, stratified sampling, and data augmentation.Good applied statistics skills, such as distributions, statistical testing, regression, etc. Bayes rule, Hypothesis tests.Minimum requirements:Passion and enthusiasm for data science and machine learning.3+ years of experience researching and/or developing applications in Python.2+ years of experience solving data science problems in Python (Scikit-learn, TensorFlow, Keras, Pytorch, Pandas, Numpy, MatplotLib).Demonstrable experience implementing supervised models using machine/deep learning techniques, including word embeddings, convolutional and recurrent neural networks, and gradient boosting.Knowledge and experience processing structured and unstructured data, especially Natural Language Processing (text extraction, text-based feature engineering, ...).Solid understanding of machine/deep learning concepts like backpropagation, gradient descent, vanishing gradient problem, data leakage, stratified sampling, and data augmentation.Good applied statistics skills, such as distributions, statistical testing, regression, etc. Bayes rule, Hypothesis tests.High level of English, written and spokenOptional requirementsMaster/Course in Data Science, Deep Learning or Machine learning (University, Udacity, Coursera..
