Experience with statistical analysis, predictive modeling, machine learning paradigm with familiarity with supervised/ under supervised techniques such as Liner Regression, Logistic Regression, KNNk-Nearest Neighbor.b.Deep understanding of modern machine learning techniques and their mathematical under pinning such as classification, clustering, optimization, deep numeral network and natural language processing.c.Strong skill in SQL and distributed system optimization e.g. Hadoop, Hive, Spark, Presto. Familiarity with Python libraries, NumPy, SciPy, pandas, Keras, Tensor Flow, scikit-learn.d.Utilizing Deep Learning techniques for advanced features engineering and model building for multimedia data e.g. how to detect patterns/ signatures/ anomalies in signal effectively.