Shadir Mohammed Online Resume

Mar 2020

Present

Senior Data Scientist

Directi Mumbai, IN

Developed Text Summarization (seq2seq model for summarizing reviews of more than 500 characters) and Sentiment Analysis on Customer Surveys using Natural Language Processing and Deep Learning Models.
Implemented various text processing techniques such as PoS Tagging, Named Entity Recognition, Cleaning and pre-processing of text documents, Text Feature Extraction using Word2Vec and BERT, Text Classification using LSTM, RNN, etc.
Built Abuse Detection Model and High-Precision Classifiers on Highly Imbalanced Dataset using Advanced Sampling Techniques and Ensemble Machine Learning Models.
Built Semi-Supervised Machine Learning Models to predict the Demand of premium domains using a Combination of Hierarchical Agglomerative Clustering and Classification Algorithms.
Built Web Scrapers for extracting data from Domain Retailers like Google, GoDaddy, etc. using Selenium and Scrapy Python Libraries.
Developed SQL Scripts to collect data from multiple tables using CTEs, Joins, Window Functions, etc.
Technologies Used: Python, NLTK, Spacy, Flask, Apache Spark, Keras, TensorFlow, RNN, LSTM, Word2Vec, BERT, Apache Kafka, Cloud Computing, Scikit Learn, Pandas, Numpy, Docker, Kubernetes, TensorFlow Serving, etc.

Nov 2016

Mar 2020

Data Scientist

Reliance Jio Mumbai, IN

Used machine learning and statistical modeling techniques to develop and evaluate algorithms to improve performance, quality, data management, and accuracy.
Developed Fraud Detection Model for Aadhaar eKYC Transactions to predict fraudulent transactions which led to 80% fewer fraudulent transactions.
Developed Customer Segmentation Algorithm using PAM Clustering to create personalized customer offers for Reliance Mart.
Performed sentiment analysis on AJIO customer reviews using sentiment-word embeddings to better understand the customer's needs and preferences, products pain points, etc.
Worked in technical teams in the development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.
Technologies Used: Python, R, Scikit Learn, MongoDB, MySQL, R Shiny, Docker, Kubernetes, TensorFlow, Keras, NLP, TF-IDF, NLTK, Pandas, Numpy, LSTM, Flask, K Means Clustering, Regression and Classification using Generalized Linear Model, Naive Bayes, Random Forest, XgBoost, Catboost, Apriori, FP-Growth, SVM, Multivariate Statistical Analysis, Model Deployment using Docker and Kubernetes, etc.

Shadir Mohammed