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· Expert in R, Python, SQL, SAS
· Professional working experience in Machine learning algorithms such as linear regression, Logistic regression, Naive Bayes, Decision Tr...
· Professional working experience in Natural Language processing algorithms for text classification, sentiment analysis, entity recognition etc for Tokenization, Stop Words, Stemming, Lemmatization, Word2Vec, Count Vectorization, TF, IDF, TF-IDF .
· Experience using various packages in R and Python like scikit - learn, numpy, pandas, Tensor flow, NLTK, spaCy, ggplot2, caret, dplyr, pROC.
· Extensive experience in Text analytics, generating data visualization using R, Python.
· Extensive experience in generating data visualization using Power BI.
· Experience in writing code in R and Python to manipulate data for data loads, extracts, statistical analysis, modelling.
· Utilized analytical applications like R and Python to identify trends and relationship between different pieces of data.
· Skilled in performing data parsing, data manipulation and data preparation with methods including describe data contents, compute descriptive statistics of data, regex, split and combine, Remap, merge, subset, reindex, melt and reshape.
· Good knowledge in Database Creation and maintenance of physical data models with Oracle and SQL Server databases
· Proficient in Statistical methods like Regression Models, hypothesis testing, confidence intervals, principal component analysis and dimensionality reduction.
· Experienced in writing complex SQL Quires like Stored Procedures, triggers, joints, and Sub quiresShow More
Data & Analytics
Digital Payment Analysis
Digital Payment Analysis is finding which wallets are being used the most. Has there been a shift from one wallet to another. What is the pain points related to digital payments? Sentiment regarding various wallets, rank the wallets, what are the positives can be built on, are there any gaps (statements like ‘I wish’).Show More Show Less
Banking Credit Risk Analysis
The Bank is rolling out Credit Risk Analysis for customers who are applied for loans. The other part of the project was to identity whether customer will pay the loan or not.Show More Show Less
Price of a property is one of the most important decision criterions when people buy homes. Real Estate firms need to be consistent in their pricing in order to attract buyers. Having a predictive model for the same will be great tool to have, which in turn can also be used to tweak development of properties, putting more emphasis on qualities which increase the value of the property.Show More Show Less
Retail is to predict whether a store should get opened or not based on certain factors such as sales, population, area etcShow More Show Less