SUMMARY

• Over 6+ years of working experience in Big Data environment including designing and building different machine learning models using Python, R and Scala.
• Proficient in managing entire project life cycle and actively involved in all teh phases of project.
• Experienced wif machine learning algorithm such aslogistic regression, random forest, KNN, SVM, neural network, linear regression, NLP and k - means
• Implemented Bagging and Boosting to enhance teh model performance and operational efficiency.
• Experience in using various packages in R and python like ggplot2, caret, dplyr, Rweka, rjson, plyr, SciPy, Scikit-learn, Beautiful Soup, NLTK, NumPy, Pandas, Dialogflow, Matplotlib.
• Comprehensive noledge and experience innormalization/de-normalization, data extraction, data cleansing and data manipulation
• Working noledge of extract, transform, and Load (ETL) components and process flow using Talend.
• Extensive experience in Text Analytics, generating data visualizations using R, Python and creating dashboards using tools like Tableau.
• Experience implementingMLback-end pipeline Spark MLlib, Scikit-learn, Pandas,NumPy.
• Experience in writing code in R and Python to manipulate data for data loads, extracts, statistical analysis, modeling, and data munging.
• Extensively worked in Cloud services such as Microsoft Azure and Amazon AWS.
• Experience in AWS (Amazon Web Services) EC2, VPC, IAM, S3, Cloud Front, Cloud Watch, Cloud Formation, Glacier, RDS Config, Route53, SNS, SQS, Elastic Cache.
• Experience in Big Data Technologies using Hadoop, Sqoop, Pig, Hive, Spark, HDFS, ADLS, Cloudera.
• Hands on experience using Spark MLlib utilities such as including classification, regression, clustering, collaborative filtering, dimensionality reduction.
• Working experience in implementing Machine Learning Algorithms using MLLib and Mahout in Hadoop ecosystem and Apache Spark framework such as HDFS, Map Reduce, HiveQL and Spark SQL.
• Hands on experience Hadoop, Deep Learning Text Analytics and IBM Data Science work bench tools.
• Hands on experience in Data Governance, Data Mining, Data Analysis, Data Validation, Predictive modeling, Data Lineage and Data Visualization in all teh phases of teh Data Science Life Cycle.
• Experience wif Data Analytics, Data Reporting, Ad-hoc Reporting, Graphs, Scales, PivotTables and OLAP reporting.
• Extensively worked for data analysis using R Studio, SQL, Tableau and other BI tools.
• Knowledge in NoSQL databases such as HBase, Cassandra, and Mongo DB etc.
• Experienced in writing complex SQL Queries like Stored Procedures, triggers, joints, and Sub queries.
• Experience working wif Web languages such as Html, CSS, Rshiny etc.
• Experience in usingSSIStools like Import and Export, Package Installation, and SSIS Package Designer.
• Expertise in usingglobal variables,expressionsandfunctionsfor teh reports wif immense experience in handling sub reports inSSRS.
• Experience inimporting/exportingdata between different sources like Oracle/Access/Exceletc. using SSIS/DTS utility.
• Definingdata warehouse(star and snowflake schema), fact table, cubes, dimensions, measures usingSQL Server Analysis Services.
• Strong written and oral communication skills for giving presentations to non-technical stakeholders.

TECHNICAL SKILLS

Programming Languages: R, Python, SQL, Scala, UNIX, C, JAVA, and Tableau.

Operating Systems: Windows, Unix, Linux

Machine Learning: Linear regression, Logistic regression, SVM, Decision tree, Random Forest, K-nearest neighbor, K means, Avro, MLbase.

Data Science tool: R,Python, MATLAB, Rshiny, Flask, Docker, Jupyter Notebook, and Azure Notebook.

Databases: MySQL, SQL Server, TSQL, MySQL, MS Access, Hive, Cassandra, MongoDB, Hadoop (HDFS).

Data Modeling Tools: Erwin 9.7, ER/Studio, Star-Schema Modeling, Star Schema, Snowflake Schema

Bigdata Framework: HDFS, MapReduce, Pig, Hive, Sqoop, Flume, HBase, Spark, Storm, Kafka, Scala.

BI Tools: Tableau, SAP, Crystal Reports, Amazon Redshift, Azure Data Warehouse, Splunk.

Cloud Technologies: AWS (EC2, S3, RDS, EBS, VPC, IAM, Security Groups), Microsoft Azure

Hands on R-Packages: tidyR, reshape2, stringR, lubridate, validate, neuralnet, ctree, rpart, tseries, randomforest, forecast, quantmode, tm.

Hands on Python Packages: Pandas, numpy, matplotlib, scipy, sklearn, Beautifulsoup, urllib2, nltk.

Pipeline Tools: Azure Data Factory, Informatica, Talend, Apache Kafka.

Other Tools and Technologies: PL/SQL, ASP, Visual Basic, Django Framework, XML, C, C++, C#, JAVA, HTML 5, CSS, JavaScript, Data bricks, ADLS,UNIX shell scripting, PERL, Ruby.

PROFESSIONAL EXPERIENCE

ML Engineer / Data Scientist

Confidential, Pierre, SD

Responsibilities:

• Working independently and collaboratively throughout teh complete analytics project lifecycle includingdataacquisition, data wrangling, data transformation, model selection and implementation of scalable machine learning models, hyper parameter tuning and documentation of results.
• Performed Statistical Analysis to determine peak and off-peak time periods for ratemaking purposes.
• Participated in all phases ofdatamining,datacollection,datacleaning, developing models, validation and visualization.
• Conducted analysis of customerdatafor teh purposes of designing rates.
• Identified root causes of problemsand facilitated teh implementation of cost-TEMPeffective solutions wif all levels of management.
• Developed Regression Models based ondataprovided by teh client.
• Application of various machine learning algorithms and statistical modeling like decision trees,regression models, clustering, SVM to identify Volume using scikit-learn package inPython.
• Worked on differentdataformats such as JSON, XML and performed ML algorithms in Python.
• Hands on experience in implementing Naive Bayes and skilled in Random Forests, Decision Trees, Linear and Logistic Regression, SVM, Clustering, Principal Component Analysis.
• Performed K-means clustering, Regression and Decision Trees in R.
• Worked on Naïve Bayes algorithms for Agent Fraud Detection using R.
• Used packages like dplyr, tidyr and ggplot2 in R Studio for datavisualization and generated scatter plot and high low graph to identify relation between different variables.
• Developed NLP models for Topic extraction, Sentiment Analysis.
• Worked on Text Analytics, Naïve Bayes, Sentiment analysis, creating word clouds, and retrieving data from Twitter and other social networking platforms
• Has noledge on A/B Testing, ANOVA, Multivariate Analysis and Association Rulesusing R.
• Wrangleddata, worked on large datasets (acquireddataand cleaned thedata), analyzed trends by making visualization (Tableau 9.0, Microsoft Power BI) using matplotlib and python.
• Implemented Predictive analytics and machine learning algorithms to forecast key metrics in teh form of designed dashboards on to AWS (S3/EC2) and Django platform for teh company's core business.
• Analyze Data and performed Data Preparation by applying teh historical model to teh data set in AZUREML.
• Used Azure Data Lake Analytics to manage on-demand pay-per-job analytics service wif enterprise-grade security, auditing and support.
• Experience wif Azure Data factoryto do data integration service to orchestrate and automate data movement and transformation.
• Hands on experience wif Azure Data bricks to manage fast, easy and collaborative Spark based analytics platform optimized for Azure
• Performeddataanalysis by using Hive to retrieve thedatafrom Hadoop cluster and SQL to retrievedatafrom Oracle database and tan used ETL fordatatransformation.

Environment: R-Studio, Python, NLP, AWS, MySQL, DB2, Metadata, Azure, Scala, Spark, Cassandra,dplyr, tidyr, ggplot2, Scikit-learn, Matplotlib, json, Machine Learning Algorithms, Mainframes MS Vision.

DATA SCIENTIST / Data Engineer

Confidential, Framingham, MA

Responsibilities:

• Lead teh full machine learning system implementation process: collectingdata, model design, feature selection, system implementation, and evaluation.
• Utilized Spark, Scala, Hadoop, HBase, Kafka, Spark Streaming, MLLib and R a broad variety of machine learning methods including classifications, regressions, dimensionally reduction etc.
• Creating various B2B Predictive and descriptive analytics using R and Tableau.
• Used text mining and NLP techniques find teh sentiment about teh organization.
• Developed unsupervised machine learning models in teh Hadoop/Hive environment on AWS EC2 instance.
• Worked wifdatasets of varying degrees of size and complexity including both structured and unstructureddata.
• Participated in all phases ofdatamining,datacleaning,datacollection, developing models, validation, visualization and performed gap analysis.
• Datawrangling to clean, transform and reshape thedatautilizing Numpy and Pandas library.
• DataStoryteller, MiningDatafrom differentDataSource such as SQL Server, Oracle, Cube Database, Web Analytics, Business Object and Hadoop. Provided AD hoc analysis and reports to executive level management team.
• Contributed todatamining architectures, modeling standards, reporting, anddataanalysis methodologies.
• Worked wif different sources such as Oracle, Teradata, SQLServer and Excel, Flat, Complex Flat File, Cassandra, MongoDB and HBase files.
• Conduct research and made recommendations ondatamining products, services, protocols, and standards in support of procurement and development efforts.
• Used Python, R and SQL to create Statistical algorithms involving Linear Regression, Logistic Regression, Random forest, Decision trees for estimating teh risks.
• Developed statistical models to forecast inventory and procurement cycles.
• Created Data Maps / Extraction groups in Power Exchange Navigator for legacy IMS Parent sources.
• Assisted in building teh ETL Source to Target specification documents by understanding teh business requirements.
• Developed mappings that perform Extraction, Transformation and load of source data into Derived Masters schema using various power center transformations like Source Qualifier, Aggregator, Filter, Router, Sequence Generator, look up, Rank, Joiner, Expression, Stored Procedure, SQL, Normalizer and update strategy to meet business logic in teh mappings.
• Used Teradata utilities like BTEQ, fast load, fast export, multiload for data conversion.
• Created Post UNIX scripts to perform operations like gunzip, remove and touch files.
• Managing teh Openshift cluster that includes scaling up and down teh AWS app nodes.
• Had strong exposure using ansible automation in replacing teh different components of Openshift likeECTD,MASTER, APP, INFRA,Gluster.

Environment: R Studio 3.5.1, AWS S3, NLP, EC2, Neural networks, SVM, Decision trees, MLbase, ad-hoc, MAHOUT, NoSQL, MDM, MLLib & Git, Informatica, OpenShift, Teradata 14, Hadoop Map Reduce, Pyspark, Spark, R, Spark MLLib, Tableau, Cassandra, Oracle, MongoDB, Flat Files, XML, and Tableau.

SQL DEVELOPER/Data Analyst

Confidential

Responsibilities:

• Used DDL and DML for writing triggers, stored procedures, and data manipulation.
• Scheduling and monitoringdataimport jobs from external sources (Postgre DB hosted on AWS) using AzureDataFactoryintoAzureSQL DB.
• Interacted wif Team and Analysis, Design and Develop database using ER Diagram, involved in Design, Development and testing of teh system
• Implemented, scheduled, and monitored ETL process to importdatafrom external sources in AWS using AzureDataFactoryintoAzureSQL database
• Developed SQL Server Stored Procedures, Tuned SQL Queries (using Indexes)
• Created Views to facilitate easy user interface implementation and Triggers on them to facilitate consistent data entry into teh database.
• Implemented Exceptional Handling.
• Worked on client requirement and wrote Complex SQL Queries to generate Crystal Reports.
• Created different Data sources and Datasets for teh reports.
• Tuned and Optimized SQL Queries using Execution Plan and Profiler.
• Rebuilding Indexes and Tables as part of Performance Tuning Exercise.
• Involved in performing database Backup and Recovery.
• Documented end user requirements for SSRS Reports and database design.

Environment: SQL Server, AWS, Azure, SSIS, SSRS, Windows Server 2008, XML.