Lead Data Scientist
Wipro Technology Pvt. Ltd. Pune, India
Total years of experience :9 years, 4 Months
• Developed asset health care solution to avoid unplanned maintenance & plant shutdown by building anomaly detection system using deep learning model like Auto encoder with Python for Oil & gas plants sensor data.
• Build Question-Answering Chatbot using PEFT- QLORA based fine tuning Llama-2 LLM model with LangChain framework and FAISS library over the documents. To provide information, answers about the Oil & gas industry, such as environmental impact, safety and regulations.
• Predict machine utilization to optimize machine usage in order to reduce their spending using Time Series Forecasting based on deep learning hybrid (CNN - LSTM) model with Python Programming.
• Developed System for Sales Unit Demand Forecasting using Time Series Forecasting based Machine Learning and Deep Learning models like (Random Forest, XG Boost, NNAR, LSTM, Ensemble) to do localization planning for Retail client with R & Python programming.
• Promotion Analysis on Retail Products using Machine Learning based Lasso Regression and XG Boost Models in R programming.
• Build Customer Journey Machine learning Regression models to predict Who, What & When will do likely activity for Airline Clients loyalty data with R & Ordinal Logistic, Nominal multinomial, Negative Binomial Regression Models.
• Build revenue analysis and offer recommendation system for Telecom Clients campaign services using Statistical methodologies- Factor analysis, ANOVA, t-test & Gamma association with R programming.
• Developed Predictive Machine Learning models for Stock closing price prediction for US based coffee client with Spark, MLP based Neural Network with Scala & R.
• Performed Text & Sentiment Analysis with data pre-processing using R and data ingestion, storage, querying using HDFS, Flume and Hive.
• Build Predictive Machine Learning model for telecom client to predict complaint repetition probability with GLM & Random Forest machine learning models with R & Hive.
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