Venkata Vamsi Krishna Bhuvanam - Data Scientist - Resume

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Venkata Vamsi Krishna Bhuvanam - Resume - Data Scientist - Deep Analytics Experience in Deep Analytics and ability to portray the findings in D3.js, High Charts and Charts Js dashboards which update the real-time data dynamically.
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    VENKATA VAMSI KRISHNA BHUVANAM Marina Del Rey, CA | (816)-745-3142 | [email protected] | github.com/bvvamsik | linkedin.com/in/bvvamsik PROFESSIONAL SUMMARY    Analyzed and created dimensional data modeling to meet OLAP needs of Medical Records dispatch project    Redesigned a web-based pivot-table application to perform the business strategy layout    Implemented data visualizations using D3.JS for infrastructural components    Deployed Node.JS and D3.JS applications in the IBM Bluemix Cloud Platform Intelligence stack    Experience in Python, Java, C++ and object oriented programming concepts, SQL and R programming languages      Experience in Software development lifecycle using Agile and Waterfall methodologies      Experience in Dashboard creation using JavaScript and Angular JS for dynamic development      Excelled under lead consultant and developer in analyzing, architecting, developing and documenting the various applications in Capgemini ’s Financial Services for Credit Cards and Payments Business along with Media Analytics  TECHNICAL SKILLS    Java, C, C++, C#, JavaScript, D3.JS, R, Python, Classic ASP/VBScript, HTML, XML, CSS3, jQuery, AJAX    Android SDK, Jenkins, Angular JS, Node.JS, Ionic Framework, Apache Spark, Hadoop, Machine Learning      MS Excel, MS PowerPoint, MS Access, SQL, MySQL, Mongo DB, NoSQL, dashDB, IBM Bluemix, ETL    JSON, Kibana, Google Analytics, Tableau, Omniture/Adobe Analytics, Flurry, Localytics    UNIX, Linux, Windows 98 / XP / 7 / 10, Root Cause Analysis, HP Quality Center, HP QTP, Selenium, JMeter, JUnit EDUCATION    Masters of Science in Computer Science (Data Science),   Dec 2016   GPA: 3.6/4.0 University of Missouri - Kansas City, Kansas City, MO    Bachelor of Technology in Computer Science & Engineering , May 2011 GPA: 3.7/4.0  Jawaharlal Nehru Technological University, Kakinada, India WORK EXPERIENCE Capgemini India Pvt Ltd APR 2012  –  MAY 2015 Associate Consultant  JUN 2014 –   MAY 2015      Developed dashboards by collaborating with database team to measure quality metrics    Automated data collection by building tools to integrate the project management data from various platforms    Collaborated with Business Intelligence team to develop dashboards and build alert systems, models for insights    Created software modules to replicate real-time scenario to calculate risk assessment of merchant    Involved in managing team and handled resource shortage, by cross application training & Knowledge Transfers    Preparation of LOEs for upcoming releases and change requests.    Created tools using VBA for tracking defect density and other metrics directly from HP Quality Center Senior Software Engineer  JUN 2013 –   MAY 2014    Developed solutions using Java to parse XML document for fraud detection and merchant onboarding      Implemented dashboards, escalations and alerts to ensure continuity and advancement    Created, developed and managed automation scripts for operational and monitoring tasks    Implemented root cause analysis (RCA), risk management processes in development phase to improve quality Software Engineer  APR 2012 –   MAY 2013    Worked on Credit Cards domain in Financial Services, involved in cross verification and validation of back-end applications on Vision Plus technology.    Designed tool using VBA to upload test suites to HP Quality Center to reduce manual efforts    Designed and created dashboards using API calls and NoSQL (MongoLab) to save and extract the data    Created dashboards for analysis of testing phase and quality metrics to identify the quality of the product    Designed a standard document process to stakeholders for education and collaboration    VENKATA VAMSI KRISHNA BHUVANAM  –  Page 2 PROJECTS Predicting Infant Mortality Rate using Naïve Bayes Classifier Spring 2017      Technologies:  R, CSV Editor, Python, Django    The goal is to predict infant mortality rate using Naïve Bayes Classifier    Collected public data from World Bank, centers for disease control & prevention and world health organization datasets, performed analysis and portrayed using D3.js and high charts. Drug recommendation system using Knowledge Base Summer 2016      Technologies:  Apache Spark, SWQRL, Apache Jena Fuseki Server, Ontology, Protégé, NLP, Ionic framework    The goal of this project is to create a knowledge base and recommendation system using Natural Language Processing (NLP) and Random Forests for classification data    Collected dataset on diseases and drugs, using machine learning algorithms create dynamic Ontology    Performed MAP Reduce algorithms and cleaned the data and performed several algorithms like random forest and decision trees to create a dynamic Ontology.    Performed analysis for different machine learning approaches, portrayed the performance of algorithms on dataset Recommendation system (songs) based on facial expressions Spring 2016      Technologies:  Apache Spark, Android, R, Smart Watch.    The goal of this project is to recommend songs to a person using decision tree algorithm based on his/ her facial expressions. Images are sent using spark streaming using Android-Socket programming for high performance    This Project is a recommendation system which observes the person ’ s facial feelings by sending the images using spark streaming to server using Android-Socket programming    The important aspect of this project is to help patient to recover in better way by implementing Machine learning (MLLIB) and NLP techniques in Scala and recommend songs based on user profile Predicting Shortest Path in the Presence of Congestion Fall 2016      The goal of this project is to find the shortest path for given data in text format with Edge weights, Flow Weights, Capacity weights; designed and provided approaches based on city and depending on congestion strength    Designed and provided many approaches based on city and depends on congestion strength in a particular area    Analyzed the design under many circumstances and designed an algorithm and visualized using google analytics    Tested and checked the robustness of the algorithm with many advanced methodologies    Built complete solution in python which returns recommendation of the shortest path after considering congestion Automated Patient Medical Record Dispatch Spring 2016      Technologies:  Ionic Framework, FileStack API, MLab, Cordova, HTML5, CSS3    This application will help to reduce the gap and paperwork involved in medical tests ordered by doctors to diagnostic centers and also a fast and reliable service with security features which will not leak medical records    This is a hybrid application used both on desktops, mobile web and mobile application which can be used to raise requests for medical tests, upload/download reports for tests    Designed backend with Mongo Lab as database and FileStack API as file server with security API keys Android Application for Face Detection Fall 2015      Technologies:  HTML5, CSS3, FacePlusPlus API, Ionic Framework, Node.JS, Angular JS, Android SDK, IBM Bluemix    This is a type of generic gallery application in mobile where it has access to all images which will also detect faces in those images using Face++ and compare those images to contact pictures and get the contact details    This application helps the developer to check the analysis of the face detection in different light shades, which helps the application to train itself to make it robust ACHIEVEMENTS    Received “Propellers Award” and Team Player Award at Capgemini for leading cross application training  
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