1. Experience in Machine Learning and Deep Learning, including regression,
classification, neural network, and Natural Language Processing (NLP).2. Extensive experience on Natural Language Processing (NLP) libraries such as Spacy, NLTK, flair, and sklearn-crfsuite.3. Strong background in DNN, CNN, RNN(LSTM), GAN, and libraries to deploy these models, such as Sklearn, Keras, Pandas, and TensorFlow.4. Experience in Text Analytics, developing different Statistical Machine Learning, Data Mining solutions to various business problems, and generating data visualizations using R, Python.5. Experience with common data science toolkits and libraries, such as Pandas, NumPy, SciPy, Scikit-learn.6. Experience with data exploration to find actionable insightsand make Product Recommendations through Funnel Analyses, A/B testing, Churn analysis, User Segmentation, Retention Rate, and business KPIs.