1. Train and Built sequence to sequence Deep Learning model for generating text and understanding language for more human like conversation. 2. Experience in Object oriented programming, Client/Server Application, Relational and non-relational Database, HDFS, Object Relational Mapping, Event driven programming, Map reduce design, graph data structure: Shortest Path, BFS, Topological Sort, PageRank etc. on huge dataset. Also have experience in designing scalable architecture on distributed system. 3. Handle Data pipeline task right from setting data preprocessing - Imputing missing value, handling categorical dataset, L1 regularization (handle over fitting), Dimension reduction (PCA, LDA) and tuning up the hyper parameter. 4. Experience in working with Convex Optimization problem using LaGrange’s Multiplier 5. Finding of semantic similarity between similar context which provide in-depth relation to the context using Knowledge Graph (provided by http://dbpedia.org/) along with Word similarity using WordNet database provide by NLTK. 6. Created Maxent model for multi class document classification and used Stanford NLP library for understanding sentence ontology and classifying based on ontology class and concept. 7. Time series analysis (Autoregression using ARIMA) for predicting storage usage of Hard drive for individuals and the available drive space on a particular timeline. 8. Prediction of drives failure using SMART data to replace and back up of the disk to improve reliability of the RAID array. 9. Experience in working with NLP library like rasa for intent and entity extraction that can be used in chatbot, spacy for NER, POS. NLTK for generating parse tree along with key phrase extraction. 10. Experience in building product at scale using machine learning algorithm capable to handling large data on a distributed platform with python. 11. Familiar with distributed design and architecture with python using library such as Blaze, mrjob, Spark, etc.