Statistics :
- Sound knowledge of statistics including (but not limited to) probability distributions, sampling techniques, correlations, parameter estimation, hypothesis testing etc.
Machine Learning :
- Theoretical understanding of key machine learning concepts and algorithms including (but not limited to) loss functions, supervised classification, clustering, feature selection, optimization, ensemble methods, evaluation metrics etc.
- Practical experience with application of these in the areas of information extraction, retrieval, natural language processing, recommendation or other is desirable.
- Proficiency in one of these programming languages - R / Python / Java / Scala. Familiarity with one or more key math and ML libraries in the language of choice.
- Working knowledge of Hadoop, Spark including terminal commands and key concepts like RDDs, data frames etc. are expected.
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