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Role:
Gather relevant information to define the business problemCreative thinker capable of linking AI methodologies to identified business challengesDevelop AI/ML applications leveraging the latest industry and academic advancementsAbility to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You: Demonstrated passion for AI competing in sponsored challenges such as KagglePrevious experience with or exposure to:Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQLBig Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learningClassical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means,Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks Feedforward, CNN, LSTMs GRUs is a plus. Optimization techniques Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processingDeep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plusConcentration in Computer Science.
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