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…)Python scripts for automation, unit tests, deploymentExperience with NLP python libraries like NLTK, Gensim, GluonNLP, Beautiful-SoupExperience with state-of-the-art python libraries like Dask, Hyperas, FlairVisualization libraries and frameworks like Seaborn, Bokeh, D3.js, GGplot, PlotlySemi-supervised and unsupervised training, reinforcement learningDevelopment of custom loss functions and metrics for neural network modelingML-based application deployment: Web Server Gateway Interface, Flask, Django, Apache server, Docker, KubernetesExperience with Java, C++, PHP, Matlab/OctaveUniversity degree or its equivalentWeb-based interfaces: Javascripts, node, angular, reactExperience with SQL and NoSQL databasesKnowledge of classical Artificial IntelligenceExperience with distributed TensorFlow (CPUs, GPUs, TPUs)Experience with Big Data: PySpark / Scala,Other: GIT / Linux / Bash (public repository with data science projects)Soft Skills:Team worker; ability to work with teams distributed geographically in different locationsProactive, motivated and willing to consolidate and develop a professional careerAnalytical, logical and critical thinking. Solid problem-solving skills: ability to identify problems and suggest mitigating and contingency actionsExpert ability to work independently and manage one's timeAbility to deal with ambiguous situationsPractical, committed, open-minded, and positiveAdvisory skillsOptional requirementsMaster/Course in Data Science, Deep Learning or Machine learning (University, Udacity, Coursera…)Python scripts for automation, unit tests, deploymentExperience with NLP python libraries like NLTK, Gensim, GluonNLP, Beautiful-SoupExperience with state-of-the-art python libraries like Dask, Hyperas, FlairVisualization libraries and frameworks like Seaborn, Bokeh, D3.js, GGplot, PlotlySemi-supervised and unsupervised training, reinforcement learningDevelopment of custom loss functions and metrics for neural network modelingML-based application deployment: Web Server Gateway Interface, Flask, Django, Apache server, Docker, KubernetesExperience with Java, C++, PHP, Matlab/OctaveUniversity degree or its equivalentWeb-based interfaces: Javascripts, node, angular, reactExperience with SQL and NoSQL databasesKnowledge of classical Artificial IntelligenceExperience with distributed TensorFlow (CPUs, GPUs, TPUs)Experience with Big Data: PySpark / Scala,Other: GIT / Linux / Bash (public repository with data science projects)Soft Skills:Team worker; ability to work with teams distributed geographically in different locationsProactive, motivated and willing to consolidate and develop a professional careerAnalytical, logical and critical thinking. Solid problem-solving skills: ability to identify problems and suggest mitigating and contingency actionsExpert ability to work independently and manage one's timeAbility to deal with ambiguous situationsPractical, committed, open-minded, and positiveAdvisory skillsLanguage requirements:EnglishLevel of experience (years):Mid Career (2+ years of experience)Tagged as: Data Mining , Industry , Spain#J-18808-Ljbffr
