Data Scientist | NLP Researcher | AI practitioner | Machine Learning | Deep Learning | Data Engineering | Software Engineering Performance-focused Data Scientist with 7 years of in-depth expertise in cutting-edge AI, Machine Learning, Deep Learning, NLP, Search & Recommendations, Text Mining, Large-Scale (Big Data) Distributed Systems, and Cloud computing. In the past five years, engineered and productized two successful AI hyper-scaled platforms (AI powered conversational Chabot and Big data Analytics Platform for Cyber Security). The game-changer in these AI platforms is the laser-sharp client personalization powered by the state-of-the-art AI NLP systems and Search systems proposing personalized recommendations to users with near to zero false positive response. Involve in multiple phases of the project starting from Requirements gathering, Architecture design, POC and Production deployment: NLP Researcher/Developer - Extensively worked on state-of-the-art NLP include: o Question/Answering, Information Extraction and Retrieval, Ranking, Search & Recommendations. o Natural Language Inference (Roberta, BART), Semantic Textual Similarity, Duplicate Identification o Conversational Chabot's, Dialogue Handling, Language Modeling, Next Word Prediction. o Text embedding (BERT, Bio-BERT, Distil BERT Sentence Transformer, TFIDF, One Hot Encoding). o Coreference resolution, Dependency Parsing, NER, POS tagging, n-grams, Topic Modeling. Machine Learning Engineer: o Phishing & DGA URL classifier using Random Forest, LSTM based RNN. o User behavior analysis, Single metric Anomaly detection in time series data using one-Class-SVM. o Sentence pair classification, sentiment analysis o Similar document grouping, clustering of unstructured data Data Engineering: o Data Collection – File-beat, Metric-beat, Syslog Server, Rest API, Application logs. o Data Parsing – Data Modeling, Data parsing, Data validation, Logstash. o Data Indexing/Storing – MySQL, MongoDB, Elastic Search, Amazon S3, Kafka (Streams, KSQL) o Data Visualization – Charts, EDA, Kibana, Graphs, Dashboard Software Engineering: o ML model deployed as API using flask & Django on cloud-based architecture as docker container. o Extensive use of cloud technologies (Azure, AWS, GCP) o Created the offline batch-based approach for continues training and prediction using celery. o Calculated the severity and risk score for different anomalies to reduce false positive in production. o Continues feedback loop to retrain machine learning algorithm to improvise model performance.