Machine Learning Architect

Saxon Global Inc.
Saxon Global Inc.

Job Overview

Hi, Please reply with your updated resume and expected compensation. Feel free to contact me on for more information Machine Learning Architect Mason, OH Number of position 2 Job Description Required SkillsExperience Strong Machine Learning experience, some of which is within established technical organizations with production systems. Deep understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Experience in at least one of these toolkits Python, R, Weka, SciKit-learn, MATLAB Familiarity with machine learning frameworkslibrariespackagesAPIs (e.g., Theano, Spark MLlib, H2O, TensorFlow, PyTorch, etc.) Proven experience in ETL, data processing, transformation, cleaning, and data warehousing techniques Experience with applied statistics skills, such as distributions, statistical testing, and regression Experience with widely used probability methods (conditional probability, Bayes rule, likelihood, independence, etc.) Experience with time series analysis Experience with data visualization techniques and tools (e.g., D3JS, ggPlot2) Good software engineering background (OOP, data structures, algorithms, computability, and complexity) Excellent conversation and communication skills able to present on research and tools Masters in a relevant quantitative field, such as statistics, operations research, or computer science, depending on position level (master’s preferred) Passionate, Innovative Desired SkillsExperience Experience Building Models, and training a deep Neural Net Experience with Convolutional Neural Networks (CNN) Proven understanding of multivariable calculus and linear algebra Experience dealing with massive data sets, using big data tools (Hadoop HDFS, MapReduce, Accumulo, Presto, MongoDB, Cassandra, HBase, R, Mahout, Pig, and Hive, DCOS) Hands-on experience and expertise with cloud computing services (AWS, Azure, etc.) Responsibilities Apply data mining and machine learning techniques, perform statistical analysis, and build high-quality prediction systems that solve our customers’ business problems Explore, interpret, and analyze datasets for patterns of interest Work closely with various teams to understand our customers’ needs, eventually crafting and pitching machine learning use cases to them Model business problems to machine learning ones, map business data to dependent and independent features, perform proper feature engineering, iterate with different predictive models, and conduct hyper parameter optimization to yield highest prediction accuracy to deploy the model to production Keep up to date with latest technology trends in machine and deep learning and quickly learn about new frameworkstechniques to be used in projects delivery. Thanks Regards Santosh Direct Office X 362 Email mailtoMachine Learning Architect 1

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