Description
SUMMARY: * 3+years of working experience as a data analyst with newly acquired skills in data science and the ability to identify fine points of information in the sea of data. * Good Hands on Exposure with Insurance and financial domains. * Experience in Data gathering, cleansing, Analyzing, visualizing and predicting business outcomes. * Expertise in Weka 8.9 and various machine learning algorithms such as clustering, classification, SVM etc., * Expertise in data modelling and mapping. * Ability to perform action rule mining from dataset using Lispminer. * Experience extracting and processing data across domains and across servers. * Experienced in business prediction and providing recommendation and creating reports while managing complex internal and external data analysis responsibilities. * Web scraping skills for data extraction using jsoup, Beautiful soup. * Experience performing Data-Intensive Text Processing with MapReduce in hadoop-2.7.2 environment. * Experience in writing excel VBA macros. * Extensive experience in Release/Change Management, Project Management, Business Process Modeling, Business Requirements, writing technical specifications, Complete Software development life cycle. * Expertise in reporting tools SSRS. * SSIS skills to facilitate importing and exporting of files. * Knowledge of Data Warehouse and ETL architecture. * Experience in using AWS for modular SAS Solution. * Experience in writing SQL database Queries, Stored procedures in SQL Server. PROFESSIONAL SUMMARY: Client : AXA equitable, Chennai INDIA Duration: July 2013 to Dec 2014 Role : Data analyst Project : Middleware Description: EIB RealTime is one of the portfolios in Corporate Technology Office area of AXA. EIB stands for Enterprise Integration Bus. EIB RealTime comprises of Two Verticals viz: Entitlement Engine & Middleware. Entitlements Engine consists of Central Security Services, Oblix and LDAP. Roles & Responsibilities: * Perform analysis of the given data by predictive modelling and draw accurate inferences by visualizing the data in Tableau and generate reports by using SSRS, in accord with the objectives of the analysis. * Querying the large datasets from upstream systems (Teradata 14.10) and transforming the same and loading it to the analytical software like R, Rapid miner for predictive modelling (using linear and logistic regression). * Evaluate the given problem, situation and crisis investigating for solutions using data analysis practices by using R and prepare analysis reports by using Tableau and SSRS. * Gather data required to conduct analysis from several sources, compile it together in prescribed format and pre-process the data in R and enter the data in several data analysis software and reporting tools to generate reports. * Created business requirement documents and test documents.
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