Job Overview
Looking for a data scientist who is well versed in Machine Learning and Statistical ModelingAnalysis. Candidates would have either a B.S. Degree directly in Machine Learning or Data Science (a newer trend), or a B.S. in Computer Science, statistics or some general engineering degree, and an M.S. in Computer Science. Required Keywords and Concepts the candidate MUST know and we will go into details during an interview Python 3.x and ldquoRrdquo programming Python libraries NumPy, Panda, SciPy, SciKit-Learn, PyCharm Machine Learning Models and Algorithms Naiumlve Bayes Classification, LinearLogistic Regression, K-Nearest Neighbors, Feature Engineering, SVM, Decision Trees and Boosting, Clustering (K-Means and Gaussian Mixture Models) Statistical Modeling Analytical Methods (like PCA, Exploratory Data Analysis, Regression Trees, etc) Forecasting, Predictive modeling NoSQL databases (like Mongo) Hadoop Spark Hive AWS These are things that should be there as well and would be very good to have Network Analysis ModelsAlgorithmsTools Centrality, Degree, Betweenness, Closeness, Clustering, Degree Distribution, Assortative mixing, Modularity, Random graphs, Erdos-Renyi graphs, Stochastic Block Models TensorFlow, AirFlow, Presto Jupyter or SageMaker Notebooks Kafka Kubernetes AB Testing Data Visualization Tableau, MATLAB, Not required but a big bonus Network knowledge (TCPIP) IT Security knowledge (Logs, SIEM) Experience presenting, teaching, explaining the above
Job Detail
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