NLP System Engineer

• Nov 2021 - Present

Building, Scaling and Productionizing NLP microservices in the domain of Oncology Building, Scaling and Productionizing NLP microservices in the domain of Oncology

NLP Engineer

• Dec 2020 - Nov 2021

Working in the Digital Innovation Lab. Building Presentation Attack Detection System and NLP as a Service Platform for Digital automation Working in the Digital Innovation Lab. Building Presentation Attack Detection System and NLP as a Service Platform for Digital automation

Staff ML Engineer

• Jan 2020 - Dec 2020

Worked in the Competitive Intelligence team. Developed and tested symbolic and neural search engines for competitor news consumption. Integrated a text summarization component to the design to search and summarize relevant articles. Built parallel and generic web crawlers to create a database of competitor articles, new developments, datasheets etc Worked on log file parsing automation and developed the client for the entire ETL pipeline Developed a storage parameter… Show more Worked in the Competitive Intelligence team. Developed and tested symbolic and neural search engines for competitor news consumption. Integrated a text summarization component to the design to search and summarize relevant articles. Built parallel and generic web crawlers to create a database of competitor articles, new developments, datasheets etc Worked on log file parsing automation and developed the client for the entire ETL pipeline Developed a storage parameter optimization system for architecture team using deep Q reinforcement learning (Partially Observable Markov Decision Processes) Show less Worked in the Competitive Intelligence team. Developed and tested symbolic and neural search engines for competitor news consumption. Integrated a text summarization component to the design to search and summarize relevant articles. Built parallel and generic web crawlers to create a database of competitor articles, new developments, datasheets etc Worked on log file parsing automation and developed the client for the entire ETL pipeline Developed a storage parameter… Show more Worked in the Competitive Intelligence team. Developed and tested symbolic and neural search engines for competitor news consumption. Integrated a text summarization component to the design to search and summarize relevant articles. Built parallel and generic web crawlers to create a database of competitor articles, new developments, datasheets etc Worked on log file parsing automation and developed the client for the entire ETL pipeline Developed a storage parameter optimization system for architecture team using deep Q reinforcement learning (Partially Observable Markov Decision Processes) Show less

Data Scientist

• May 2018 - Jan 2020

Areas worked on are automatic content tag generation, medical article readability classication, article text summarization, recommendation system and topic modeling Worked on Readability Classification of the Univadis articles project end to end starting from web scraping multiple websites like The Cochrane Database of Systematic Reviews,PubMed etc., preprocessing, feature engineering, feature selection, model building and Hyperparameter tuning. Automated the Hyperparameter Tuning using… Show more Areas worked on are automatic content tag generation, medical article readability classication, article text summarization, recommendation system and topic modeling Worked on Readability Classification of the Univadis articles project end to end starting from web scraping multiple websites like The Cochrane Database of Systematic Reviews,PubMed etc., preprocessing, feature engineering, feature selection, model building and Hyperparameter tuning. Automated the Hyperparameter Tuning using Bayesian Optimization. Used both manually annotated data with the help of content team and semi supervised learning( pseudo labeling and active learning) to come up with the truth labels. Implemented a project on understanding the reading behaviour of HCP's using topic modeling and built a custom preprocessing and multilingual LDA modeling pipeline Worked on building custom bio word embeddings and entity embeddings trained on in-house data. Also worked on hypothesis testing, statistical modeling, generalized linear models, unsupervised machine learning in HCP targeting, Propensity Score Matching and digital campaign measurements using Ancova. Have implemented end to end projects involving web scraping, building custom preprocessing pipelines, feature engineering and feature selection,model building and hyperparameter tuning. Classical Machine Learning Algorithms frequently used are Logistic Regression,One Class SVM,Decision Trees, LightGBM, XGBoost, Random Forest,Correspondence Analysis, PCA, SVD, K-Means and Hierarchical Clustering Deep Learning Algorithms explored are RNN, Bidirectional LSTM,GRU, Attention, Memory Networks and Transformers Tools worked on are Python ( Libraries: Numpy, Pandas, SkLearn, Gensim, Frameworks TensorFlow, PyTorch, web scraping tools like Selenium and Beautiful Soup),R, SQL, Snowflake Show less Areas worked on are automatic content tag generation, medical article readability classication, article text summarization, recommendation system and topic modeling Worked on Readability Classification of the Univadis articles project end to end starting from web scraping multiple websites like The Cochrane Database of Systematic Reviews,PubMed etc., preprocessing, feature engineering, feature selection, model building and Hyperparameter tuning. Automated the Hyperparameter Tuning using… Show more Areas worked on are automatic content tag generation, medical article readability classication, article text summarization, recommendation system and topic modeling Worked on Readability Classification of the Univadis articles project end to end starting from web scraping multiple websites like The Cochrane Database of Systematic Reviews,PubMed etc., preprocessing, feature engineering, feature selection, model building and Hyperparameter tuning. Automated the Hyperparameter Tuning using Bayesian Optimization. Used both manually annotated data with the help of content team and semi supervised learning( pseudo labeling and active learning) to come up with the truth labels. Implemented a project on understanding the reading behaviour of HCP's using topic modeling and built a custom preprocessing and multilingual LDA modeling pipeline Worked on building custom bio word embeddings and entity embeddings trained on in-house data. Also worked on hypothesis testing, statistical modeling, generalized linear models, unsupervised machine learning in HCP targeting, Propensity Score Matching and digital campaign measurements using Ancova. Have implemented end to end projects involving web scraping, building custom preprocessing pipelines, feature engineering and feature selection,model building and hyperparameter tuning. Classical Machine Learning Algorithms frequently used are Logistic Regression,One Class SVM,Decision Trees, LightGBM, XGBoost, Random Forest,Correspondence Analysis, PCA, SVD, K-Means and Hierarchical Clustering Deep Learning Algorithms explored are RNN, Bidirectional LSTM,GRU, Attention, Memory Networks and Transformers Tools worked on are Python ( Libraries: Numpy, Pandas, SkLearn, Gensim, Frameworks TensorFlow, PyTorch, web scraping tools like Selenium and Beautiful Soup),R, SQL, Snowflake Show less

Analytics Consultant

• Apr 2017 - Jun 2017

Use data analytics to facilitate decision making and strategy development process for Branch Banking Use data analytics to facilitate decision making and strategy development process for Branch Banking

Junior Engineer

• Mar 2015 - Nov 2015