SUMMARY:

• Over 8 Year's experience in Data Analysis, Data Profiling, Data Integration, Migration, Data Governance and Metadata Management, Master Data Managementand Configuration Management.
• Experience in various phases of Software Development life cycle (Analysis, Requirements gathering, Designing) with expertise in documenting various requirementspecifications, functionalspecifications, Test Plans, Data Validation, Source to Target mappings, SQL Joins, Data cleansing.
• Extensive experience in Text Analytics, developing different Statistical Machine Learning, Data Mining solutions to various business problems and generating data visualizations using R, Python.
• Expertise in transforming business requirements into analytical models, designing algorithms, building models, developing data mining and reporting solutions that scale across amassive volume of structured and unstructured data.
• Documenting new data to help source to target mapping. Also updating the documentation for existing data assisting with data profiling to maintain data sanitation, validation.
• Experience in conducting Joint Application Development (JAD) sessions for requirements gathering, analysis, design and Rapid Application Development (RAD) sessions Experience working on Data quality tools Informatica IDQ (9.1), Informatica MDM (9.1).
• Collaborated with the lead Data Architect to model the Data warehouse in accordance with FSLDM subject areas, 3NF format, and Snowflake schema.
• Proficient in SAS/BASE, SAS EG, SAS/SQL, SAS MACRO, SAS/ACCES.
• Experience in end - to-end implementation of data warehouse project based on the SAS EG.
• Experience in extract data from adatabase such as DB2, Oracle, and SME-IM, MAD, M240 and UNIX server using SAS.
• Extensive knowledge of Hadoop eco-system technologies like Apache Pig, Apache Hive, Apache Sqoop, Storm, Kafka, Elastic Search, Redis, Flume and Apache HBase.
• Experienced in analyzing data using HiveQL and Pig Latin and custom MapReduce programs in Java.
• Experienced in writing Pig UDF and Hive UDF and UDAFs in the analysis of data.
• Extensive experience in Hive, Sqoop, Flume, Hue and Oozie.
• Created practical predictive models with machine learning methods including Supervised (linear regression, logistic regression, decision tree, random forests, SVM etc.) and Unsupervised
• Knowledge in Business Intelligence tools like Business Objects, Cognos, Tableau,and OBIEE
• Experience with Teradata and big data as the target for data marts worked with BTEQ, Fast Load and Multi-Load.
• Good knowledge in using all complex data types in Pig and MapReduce for handling the data and formatting it as required.
• Integration Architect & Data Scientist experience in Analytics, BigData, BPM, SOA, ETL and Cloud technologies.
• Built Coe competencies in the area of Analytics, SOA/EAI, ETL and BPM.
• Experience in foundational machine learning models and concepts: regression, random forest, boosting, GBM, NNs, HMMs, CRFs, MRFs, deep learning.
• Experience in machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
• Good knowledge of Hadoop architecture and its components like HDFS, MapReduce, Job Tracker, Task Tracker, Name Node and Data Node.
• Collaborated with the lead Data Architect to model the Data warehouse in accordance with FSLDM subject areas, 3NF format, Snowflake schema.
• Working knowledge of DICOM and Problem Loan Management applications.
• Highly skilled in using Hadoop (pig and Hive) for basic analysis and extraction of data in the infrastructure to provide datasummarization.
• Highly skilled in using visualization tools like Tableau, ggplot2,and d3.js for creating dashboards.
• Skilled in System Analysis, E-R/Dimensional Data Modeling, DatabaseDesign and implementing RDBMS specific features.
• Worked with HBase which is a NoSQL, column-oriented database.
• Experienced in importing and exporting data from therelational database into HDFS using Sqoop.
• Mapping and tracing data from system to system in order to establish data hierarchy and lineage.
• Using Data Lineage and reverse engineering as a way to track back errors in data till the data source.
• Experience in designing starschema, Snowflakeschema for Data Warehouse, ODSarchitecture.
• Experience in designing stunning visualizations using Tableau software and publishing and presenting dashboards, Storyline on web and desktop platforms.
• Having good experience in NLP with Apache, Hadoop and Python.
• Experience working with data modeling tools like Erwin, PowerDesigner and ERStudio.

TECHNICAL SKILLS:

Languages: T-SQL, PL/SQL, SQL, C, C++, XML, HTML, DHTML, HTTP, MATLAB, DAX, Python

Databases: SQL Server 2014/2012/2008/2005/2000, MS-Access, Oracle 12c/11g/10g/9i and Teradata, big data, Hadoop

Bigdata Ecosystem: HDFS, PIG, MapReduce, HIVE, SQOOP, FLUME, HBase, Storm, Kafka, Elastic Search, Redis, Flume, Storm, Kafka, Elastic Search, Redis, Flume and Scoop.

Statistical Methods: Time Series, regression models, splines, confidence intervals, principal component analysis and Dimensionality Reduction, bootstrapping

BI Tools: Rsoft Power BI, Tableau, SSIS, SSRS, SSAS, Business Intelligence Development Studio (BIDS), Visual Studio, Crystal Reports, Informatica 6.1.

Database Design Tools and Data Modeling: MS Visio, ERWIN 4.5/4.0, Star Schema/Snowflake Schema modeling, Fact & Dimensions tables, physical & logical data modeling, Normalization and De-normalization techniques, Kimball &Inmon Methodologies

Big Data / Grid Technologies: Cassandra, Coherence, Mongo DB, Zookeeper, Titan, Elasticsearch, Storm, Kafka, Hadoop

Tools: and Utilities: SQL Server Management Studio, SQL Server Enterprise Manager, SQL Server Profiler, Import & Export Wizard, Visual Studio.Net, Microsoft Management Console, Visual Source Safe 6.0, DTS, Crystal Reports, Power Pivot, ProClarity, Microsoft Office, Excel Power Pivot, Excel Data Explorer, Tableau, JIRA,SparkMLlib.

PROFESSIONAL EXPERIENCE:

Confidential, MountainView, CA

Data Scientist

Responsibilities:

• As an Architect design conceptual, logical and physical models using Erwin and build datamarts using hybrid Inmon and Kimball DW methodologies.
• Worked closely with business, datagovernance, SMEs and vendors to define data requirements.
• Worked with data investigation, discovery and mapping tools to scan every single data record from many sources.
• Designed the prototype of the Data mart and documented possible outcome from it for end-user.
• Involved in business process modeling using UML
• Developed and maintained data dictionary to create metadata reports for technical and business purpose.
• Involved on Prediction model building, Machine Learning, Business process improvements, Visualization & Process implementation with R Programming and DeepSee
• Redesigned and developed SAS Applications with Netezza Database to the Netezza Applications reducing run time of Applications from 40 hours to 20 sec using PostgreSQL, nzsql, Aginity Workbench, SAS
• Created SQLtables with referential integrity and developed queries using SQL, SQL*PLUS, and PL/SQL.
• Formulated procedures for integration of R programming plans with data sources and delivery systems and R language was used for prediction.
• Implementing SparkMlib utilities such as including classification, regression, clustering, collaborative filtering and dimensionality reduction.
• Design, coding, unit testing of ETL package source marts and subject marts using Informatica ETL processes for Oracledatabase.
• Developed Statistical Analysis and Response Modeling for Analytical Database contributors (logistic regression).
• Used Pig and Hive in the analysis of data.
• Used all complex data types in Pig for handling data.
• Created/modified UDF and UDAFs for Hive whenever necessary.
• Developed various QlikView Data Models by extracting and using the data from various sources files, DB2, Excel, Flat Files and Bigdata.
• Participated in all phases of datamining; datacollection, datacleaning, developingmodels, validation, visualization and performed Gapanalysis. data manipulation and Aggregation from adifferent source using Nexus, Toad, BusinessObjects, PowerBI,and SmartView.
• Handled importing data from various data sources, performed transformations using Hive, Map Reduce, and loaded data into HDFS.
• Interaction with Business Analyst, SMEs, and other Data Architects to understand Business needs and functionality for various project solutions
• Researched, evaluated, architected, and deployed new tools, frameworks, and patterns to built sustainable Big Data platforms for the clients
• Identifying and executing process improvements, hands-on in various technologies such as Oracle, Informatica, BusinessObjects.
• Loaded and transformed large sets of structured, semi-structured and unstructured data.
• Supported Map Reduce Programs those are running in the cluster.
• Managed and reviewed Hadoop log files to identify issues when ajob fails.
• Designed both 3NF data models for ODS, OLTP systems and dimensional data models using Star and snowflake schemas.
• Developed Pig UDFs for preprocessing the data for analysis.
• Involved in writing shell scriptsfor scheduling and automation of tasks.

Environment: r9.0, Informatica 9.0, ODS, OLTP, Oracle 12c/11g, Hive, OLAP, DB2, Metadata, MS Excel, Mainframes MS Visio, Rational Rose, Requisite Pro., Hadoop, PL/SQL, SAS etc.

Data Scientist

Responsibilities:

• Perform Data Profiling to learn about user behavior and merge data from multiple data sources.
• Implemented big data processing applications to collect, clean and normalization large volumes of open data using Hadoopecosystems such as PIG, HIVE, and HBase.
• Designing and developing various machine learning frameworks using Python, R, and Matlab.
• Integrate R into Micro Strategy to expose metrics determined by more sophisticated and detailed models than natively available in the tool.
• Worked on different data formats such as JSON, XML and performed machinelearningalgorithms in Python.
• Worked as Data Architects and IT Architects to understand the movement of data and its storage and ERStudio9.7
• Processed huge datasets (over billion data points, over 1 TB of datasets) for data association pairing and provided insights into meaningful data association and trends
• Developed cross-validation pipelines for testing the accuracy of predictions
• Enhanced statistical models (linear mixed models) for predicting the best products for commercialization using Machine Learning Linear regression models, KNN and K-means clustering algorithms
• Participated in all phases of datamining, datacollection, datacleaning, developingmodels, validation, visualization and performed Gapanalysis. data manipulation and Aggregation from adifferent source using Nexus, Toad, BusinessObjects, PowerBI, and SmartView.
• Independently coded new programs and designed Tables to load and test the program effectively for the given POC's using with Big Data/Hadoop.
• Develop documents and dashboards of predictions in Microstrategy and present it to the business intelligence team.
• Developed various QlikViewDataModels by extracting and using the data from various sources files, DB2, Excel, Flat Files and Bigdata.
• Good knowledge of HadoopArchitecture and various components such as HDFS, JobTracker, TaskTracker, NameNode, DataNode, SecondaryNameNode, and MapReduce concepts.
• As Architect delivered various complex OLAPdatabases/cubes, scorecards, dashboards and reports.
• Programmed a utility in Python that used multiple packages (scipy, numpy, pandas)
• Implemented Classification using supervised algorithms like LogisticRegression, Decisiontrees, KNN, NaiveBayes.
• Used Teradata15 utilities such as FastExport, MLOAD for handling various tasks data migration/ETL from OLTP Source Systems to OLAP Target Systems
• Handled importing data from various data sources, performed transformations using Hive, MapReduce, and loadeddata into HDFS.
• Collaborate with data engineers to implement ETL process, write and optimized SQL queries to perform data extraction from Cloud and merging from Oracle 12c.
• Collect unstructured data from MongoDB 3.3 and completed data aggregation.
• Perform data integrity checks, data cleaning, exploratory analysis and feature engineer using R 3.4.0.
• Conducted analysis of assessing customer consuming behaviors and discover thevalue of customers with RMF analysis; applied customer segmentation with clustering algorithms such as K-MeansClustering and Hierarchical Clustering.
• Work on outliers identification with box-plot, K-means clustering using Pandas, NumP y.
• Participate in features engineering such as feature intersection generating, feature normalize and Label encoding with Scikit-learn preprocessing.
• Use Python 3.0 (numP y, sciP y, pandas, sci-kit-learn, Seaborn, NLTK) and Spark 1.6 / 2.0 (PySpark, MLlib) to develop avariety of models and algorithms for analytic purposes.
• Analyze Data and Performed Data Preparation by applying thehistoricalmodel to the data set in AZUREML.
• Perform data visualization with Tableau 10 and generate dashboards to present the findings.
• Determine customer satisfaction and help enhance customer experience using NLP.
• Work on Text Analytics, NaïveBayes, Sentiment analysis, creating word clouds and retrieving data from Twitter and other social networking platforms.
• Use Git 2.6 to apply version control. Tracked changes in files and coordinated work on the files among multiple team members.

Environment: ER Studio 9.7, Tableau 9.03, AWS, Teradata 15, MDM, GIT, Unix, Python 3.5.2, MLlib, SAS, regression, logistic regression, QlikView.

Data Scientist..

Responsibilities:

• Data mining using state-of-the-art methods
• Extending company's data with third party sources of information when needed
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis
• Doing ad-hoc analysis and presenting results in a clear manner
• Creating automated anomaly detection systems and constant tracking of its performance
• Strong command of data architecture and data modelling techniques.
• Hands on experience with commercial data mining tools such as Splunk, R, Map reduced, Yarn, Pig, Hive, Floop, Oozie, Scala, HBase, Master HDFS, Sqoop, Spark, Scala (Machine learning tool) or similar software required depending on seniority level in job field.
• Developed scalable machine learning solutions within a distributed computation framework (e.g. Hadoop, Spark, Storm etc.).
• Utilizing NLP applications such as topic models and sentiment analysis to identify trends and patterns within massive data sets.
• Knowledge in ML & Statistical libraries (e.g. Scikit-learn, Pandas).
• Having knowledge to build predict models to forecast risks for product launches and operations and help predict workflow and capacity requirements for TRMS operations
• Having experience with visualization technologies such as Tableau
• Draw inferences and conclusions, and create dashboards and visualizations of processed data, identify trends, anomalies
• Generation of TLFs and summary reports, etc. ensuring on-time quality delivery.
• Participated in client meetings, teleconferences and video conferences to keep track of project requirements, commitments made and the delivery thereof.
• Solved analytical problems, and effectively communicate methodologies and results
• Worked closely with internal stakeholders such as business teams, product managers, engineering teams, and partner teams.

Environment: Erwin r9.0, Informatica 9.0, ODS, OLTP, Oracle 10g, Hive, OLAP, DB2, Metadata, MS Excel, Mainframes MS Visio, Rational Rose, Requisite Pro. Hadoop, PL/SQL, etc..

Data Scientist

Responsibilities:

• Statistical Modelling with ML to bring Insights in Data under guidance of Principal Data Scientist
• Data modeling with Pig, Hive, Impala.
• Ingestion with Sqoop, Flume.
• Used SVN to commit the Changes into the main EMM application trunk.
• Understanding and implementation of text mining concepts, graph processing and semi structured and unstructured data processing.
• Worked with Ajax API calls to communicate with Hadoop through Impala Connection and SQL to render the required data through it .These API calls are similar to Microsoft Cognitive API calls.
• Good grip on Cloudera and HDP ecosystem components.
• Used ElasticSearch (Big Data) to retrieve data into application as required.
• Performed Map Reduce Programs those are running on the cluster.
• Developed multiple MapReduce jobs in java for data cleaning and preprocessing.
• Developed scalable machine learning solutions within a distributed computation framework (e.g. Hadoop, Spark, Storm etc.).
• Analyzed the partitioned and bucketed data and compute various metrics for reporting.
• Involved in loading data from RDBMS and web logs into HDFS using Sqoop and Flume.
• Worked on loading the data from MySQL to HBase where necessary using Sqoop.
• Developed Hive queries for Analysis across different banners.
• Extracted data from Twitter using Java and Twitter API. Parsed JSON formatted twitter data and uploaded to database.
• Launching Amazon EC2 Cloud Instances using Amazon Images (Linux/ Ubuntu) and Configuring launched instances with respect to specific applications.
• Exported the result set from Hive to MySQL using Sqoop after processing the data.
• Analyzed the data by performing Hive queries and running Pig scripts to study customer behavior.
• Have hands on experience working on Sequence files, AVRO, HAR file formats and compression.
• Used Hive to partition and bucket data.
• Experience in writing MapReduce programs with Java API to cleanse Structured and unstructured data.
• Wrote Pig Scripts to perform ETL procedures on the data in HDFS.
• Created HBase tables to store various data formats of data coming from different portfolios.
• Worked on improving performance of existing Pig and Hive Queries.

Environment: SQL/Server, Oracle 9i, MS-Office, Teradata, Informatica, ER Studio, XML, Business Objects, HDFS, Teradata 14.1, JSON, HADOOP (HDFS), MapReduce, PIG, Spark, R Studio, MAHOUT, JAVA, HIVE, AWS..

Data Architect/ Data Modeler

Responsibilities:

• Worked with large amounts of structured and unstructured data.
• Knowledge in Machine Learning concepts (Generalized Linear models, Regularization, Random Forest, Time Series models, etc.)
• Worked in Business Intelligence tools and visualization tools such as Business Objects, Tableau, ChartIO, etc.
• Deployed GUI pages by using JSP, JSTL, HTML, DHTML, XHTML, CSS, JavaScript, AJAX.
• Configured the project on WebSphere 6.1 application servers
• Implemented the online application by using Core Java, Jdbc, JSP, Servlets and EJB 1.1, Web Services, SOAP, WSDL.
• Handled end-to-end project from data discovery to model deployment.
• Monitoring the automated loading processes.
• Communicated with other Health Care info by using Web Services with the help of SOAP, WSDL JAX-RPC
• Used Singleton, factory design pattern, DAO Design Patterns based on the application requirements
• Used SAX and DOM parsers to parse the raw XML documents
• Used RAD as Development IDE for web applications.
• Preparing and executing Unit test cases
• Used Log4J logging framework to write Log messages with various levels.
• Involved in fixing bugs and minor enhancements for the front-end modules.
• Implemented Microsoft Visio and Rational Rose for designing the Use Case Diagrams, Class model, Sequence diagrams, and Activity diagrams for SDLC process of the application
• Doing functional and technical reviews
• Maintenance in the testing team for System testing/Integration/UAT.
• Guaranteeing quality in the deliverables.
• Conducted Design reviews and Technical reviews with other project stakeholders.
• Was a part of the complete life cycle of the project from the requirements to the production support
• Created test plan documents for all back-end database modules.

Environment: R 3.0, Erwin 9.5, Tableau 8.0, MDM, QlikView, MLLib, PL/SQL, HDFS, Teradata 14.1, JSON, HADOOP (HDFS), MapReduce, PIG, Spark, R Studio, MAHOUT, JAVA, HIVE, AWS.

Confidential,

Data Analyst/Data Modeler

Responsibilities:

• Developed Internet traffic scoring platform for ad networks, advertisers and publishers (rule engine, site scoring, keyword scoring, lift measurement, linkage analysis).
• Responsible for defining the key identifiers for each mapping/interface.
• Clients include eBay, Click Forensics, Cars.com, Turn.com, Microsoft, and Looksmart.
• Designed the architecture for one of the first analytics 3.0. online platforms: all-purpose scoring, with on-demand, SaaS, API services. Currently under implementation.
• Web crawling and text mining techniques to score referral domains, generate keyword taxonomies, and assess commercial value of bid keywords.
• Developed new hybrid statistical and data mining technique known as hidden decision trees and hidden forests.
• Reverse engineering of keyword pricing algorithms in the context of pay-per-click arbitrage.
• Implementation of Metadata Repository, Maintaining Data Quality, Data Cleanup procedures, Transformations, Data Standards, Data Governance program, Scripts, Stored Procedures, triggers and execution of test plans
• Performed data quality in Talend Open Studio.
• Coordinated meetings with vendors to define requirements and system interaction agreement documentation between client and vendor system.
• Automated bidding for advertiser campaigns based either on keyword or category (run-of-site) bidding.
• Creation of multimillion bid keyword lists using extensive web crawling. Identification of metrics to measure the quality of each list (yield or coverage, volume, and keyword average financial value).
• Enterprise Metadata Library with any changes or updates.
• Document data quality and traceability documents for each source interface.
• Establish standards of procedures.
• Generate weekly and monthly asset inventory reports.

Environment: MS Office suite 2008, MS-SQL Server Management Studio 2000/2005/2008/ R2, T-SQL, DTS, Replication, Rational Rose, Windows NT, MS SQL Reporting Services 2008, MS SQL Server Analysis Services 2008, MS SQL Server Integration Services 2008, MS Access, Erwin, SQL Query Analyzer.