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Data Scientist - Natural Language Processing
Dhaval Patel
,
London, United Kingdom
Experience
Other titles
Skills
I'm offering
- 6+ years of experience in IT and comprehensive industry knowledge on Machine Learning, Artificial Intelligence, Natural Language Processing/Generation, Data Manipulation, Data Mining, Data Visualization.
- Proficient at building robust Machine Learning, Deep Learning models, Transformers, Convolution Neural Networks (CNN), Recurrent Neural Networks (RNN), LSTM using Tensor Flow and PyTorch. Adept in analyzing large datasets using Apache Spark, PySpark, Spark ML and Google Cloud Platform (AWS).
- Experience in performing Feature Selection, Linear Regression, Logistic Regression, k - Means Clustering, Classification, Decision Tree, Supporting Vector Machines (SVM), Naive Bayes, K-Nearest Neighbors (KNN), Random Forest, and Gradient Descent, Neural Network algorithms to train and test the huge data sets.
- Extensively worked on natural language processing - deep learning libraries such as Transformers.
- Proficient at building robust Machine Learning, Deep Learning models, Transformers, Convolution Neural Networks (CNN), Recurrent Neural Networks (RNN), LSTM using Tensor Flow and PyTorch. Adept in analyzing large datasets using Apache Spark, PySpark, Spark ML and Google Cloud Platform (AWS).
- Experience in performing Feature Selection, Linear Regression, Logistic Regression, k - Means Clustering, Classification, Decision Tree, Supporting Vector Machines (SVM), Naive Bayes, K-Nearest Neighbors (KNN), Random Forest, and Gradient Descent, Neural Network algorithms to train and test the huge data sets.
- Extensively worked on natural language processing - deep learning libraries such as Transformers.
Markets
United Kingdom
Industries
Language
English
Fluently
Ready for
Available
My experience
2018 - ?
job
Data Scientist
Logically.
UK
• Developed a multi document abstractive text summarization model for news
stories using denoising Sequence-to-Sequence architecture.
• Architected NLG framework that can be used to generate a title of the story.
• Developed scalable algorithm to identify automated accounts(bots) on Twitter
which can serve upto 900M requests per day.
• Developed state of the art stance detection system using ROBERTA encoder.
• Developed and deployed a classifier to identify toxic comments which can serve
upto 100K requests per hour.
• Improved f1-score of the existing click-bait detection system by 8%.
• Implemented hate speech detection model using ELMO word embeddings and bidirectional GRU along with self-attention.
• Skills Acquired: Tensorflow, PyTorch, Keras, Spacy, NLTK, MongoDB, GCP, Flask,
Kubernetes
• Developed a multi document abstractive text summarization model for news
stories using denoising Sequence-to-Sequence architecture.
• Architected NLG framework that can be used to generate a title of the story.
• Developed scalable algorithm to identify automated accounts(bots) on Twitter
which can serve upto 900M requests per day.
• Developed state of the art stance detection system using ROBERTA encoder.
• Developed and deployed a classifier to identify toxic comments which can serve
upto 100K requests per hour.
• Improved f1-score of the existing click-bait detection system by 8%.
• Implemented hate speech detection model using ELMO word embeddings and bidirectional GRU along with self-attention.
• Skills Acquired: Tensorflow, PyTorch, Keras, Spacy, NLTK, MongoDB, GCP, Flask,
Kubernetes
MongoDB, Kubernetes, Word, Tensorflow, Flask, Architecture, Twitter, Keras, Framework
2016 - 2017
job
Data Science Engineer
Tata Consultancy Services.
India
• Developed NLP framework to identify entity level sentiment.
• Improved existing default rate model's accuracy from 79% to 84.5%.
• Developed clustering algorithms/pipeline to increase precision of underlying
ML models by 10% in production.
• Awarded star performer of the quarter for developing a fraud detection model
with ROC-AUC score of 0.97.
• Skills Acquired: Scikit-learn, Logistic Regression, Clustering, Scala, S3
• Developed NLP framework to identify entity level sentiment.
• Improved existing default rate model's accuracy from 79% to 84.5%.
• Developed clustering algorithms/pipeline to increase precision of underlying
ML models by 10% in production.
• Awarded star performer of the quarter for developing a fraud detection model
with ROC-AUC score of 0.97.
• Skills Acquired: Scikit-learn, Logistic Regression, Clustering, Scala, S3
Data Science, Scala, Algorithms, NLP, Science, Production, Performer, Framework
My education
2017
-
2018
Queen Mary University of London
MSc, Natural Language Processing
MSc, Natural Language Processing
2009
-
2013
University of Mumbai
Bachelors, Computer Science
Bachelors, Computer Science
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