SUMMARY

• Having 8+years of experience in NLP/NLU/NLG/AI/machinelearning/Computer vision/Probabilistic Graphical Models/Inferential statistics/Graph Theory/System Design.
• 4 years in progress, Approved Patent in Statistical Modelling and traffic pattern analysis.
• Part of R&D team to build new analytics POC's usingApache Spark, Scala, Randmachinelearning.
• I can help you build futuristic AIbots to assist/replace human in various business domains.
• Proficientto understandofSparkcore, SparkSQL, SparkStreaming and SparkMLlib.
• Expert level understandingin ApplicationDesign, Development and testing in MainframeenvironmentsusingPL/1,COBOL,EGL,Easy Strive,DB2, JCL, QC&VAG.
• Git,Java,MySQL,MongoDB,Neo4J,AngularJS,SPSS,Tableau.
• Python,Numpy, Scikit - Learn,genism,NLTK,Tensorflow,keras.
• Experience inMachineLearning, Statistics, Regression- Linear, Logistic, Poisson, Binomial.
• Single handed built a model to replace the job of doer in thepension sector. This model (Patent under progress) generates experience from structured data and learns through a bootstrapping mechanism new experience from unseen data.
• Single handed Built and designed a whole Information extraction botPOC for KYC extraction. This bot is using adaptivelearningtechniques and uses some custom supervised classifiers for entity and relation extraction.
• Spark. Built and tested model across variousMLalgorithms to classify and score vehicles as clean/unclean.
• Experience building solutions for enterprises, context-awareness, pervasivecomputing, and/or application of machine learning
• Research and development ofmachinelearningpipeline design for OpticalCharacterRecognition (Handwritten), anomalydetectionsystem using multi variateGaussianmodel. Healthcarediagnostics systems using PGM (BN).
• Comfortable presenting to senior management, business stakeholders, and external partners.
• KBC, Chatbots, Adaptive SupervisedLearning (deterministic classification), UnsupervisedLearningmethods for IE, ANN and DeepNN for NLP and Chatbots, Probabilistic models for NLG and inferences, Decision science.
• Having hands on experience indata mining algorithms and approach.
• Having good at algorithm and design techniques.
• Experienced in Data Integration Validation and Data Quality controls for ETL process and Data Warehousing using MS Visual Studio, SSAS, SSIS and SSRS.
• Proficient in Tableau and R-Shiny data visualization tools to analyze and obtain insights into large datasets, create visually powerful and actionable interactive reports and dashboards.
• Fluency in one or more modern programming languages such as Java, C# or C++.
• Comfortable presenting to senior management, business stakeholders, and external partners.
• BS or MS degree in Computer Science or related quantitative field that relies heavily on statistics and ML software.
• Architecture and Design of reusable server components for the web as well as Mobile applications.
• Strong programming expertise (preferably in Python) and strong in Database SQL.
• Be a valued contributor in shaping the future of our products and services
• Solid coding and engineering skills preferably in Machine Learning
• Proficient in Python, experience building, and product ionizing end-to-end systems
• Knowledge of Information Extraction, NLP algorithms coupled with Deep Learning
• Exposure to python and python packages.
• Experience with file systems, server architectures, databases, SQL, and data movement (ETL).
• Experience with Hadoop systems
• Experience with Supervised or Unsupervised machine learning algorithms.

TECHNICAL SKILLS

Client-side Technologies: HTML5, PERL, Processing, Python and R, Python, Hive, C/C++, C#, Java or Python, name Bash.

MachineLearningModels: Basic Statistics,Supervised and Unsupervisedlearning.

Programming Languages: C#, VB.NET (VB6), VBScript, OOPS, Data structures, Algorithms

Frameworks: Shogun, Accord Framework/AForge.net, Scala, Spark, Cassandra, DL4J, ND4J, Scikit-learn

Development Tools: Cassandra,DL4J,ND4J,Scikit-learn,Shogun,AccordFramework/AForge.net,Mahout, MLlib,H2O,ClouderaOryx,GoLearn, Apache Signa.

BI Tools: C x 4, HBase x 4,Bash x 3,Spark x 3,ElasticSearch x 2,Data warehouse

Version Controller: TFS, Microsoft Visual SourceSafe, GIT, NUNIT, MSUNIT

Software Packages: PHP,Scala2,Shark2,Awk,Cascading,Cassandra,Clojure,Fortran,JavaScript,JMP,Mahout,objectiveC,QlickView,Redis,Redshifed

Microsoft Technologies: MS-Office 2003/ 07/10/13 , MS Access, Messaging Architectures.

Web Technologies: Windows API, Web Services, Web API (RESTFUL) HTML5, XHTML, CSS3, AJAX, XML, XAML, MSMQ, Silverlight, Kendo UI.

Web Servers: IIS 5.0, IIS 6.0, IIS 7.5, IIS ADMIN.

Operating Systems: Windows Win8/XP/NT/ 95/98/2000/2008/2012 , Android SDK.

Databases: SQL Server 2014/2012/2008/2005/2000 , MS-Access, Oracle 11g/10g/9i and Teradata, big data, Hadoop, Mahout, ML lib, H2O,Cloudera Oryx, GoLearn.

PROFESSIONAL EXPERIENCE

Confidential, MOUNTAINVIEW, CA

Machine Learning/Data Scientist

Responsibilities:

• Design and develop state-of-the-art deep-learning / machine-learning algorithms for analysing the image and video data among others.
• Develop and implement innovative AI and machine learning tools that will be used in the Risk.
• Liaise with functional lead to understand and clarify meaning and impact of key data variables.
• Effective software development processes to customize and extend the computer vision and image processing techniques to solve new problems for Automation Anywhere.
• Develop and implement innovative data quality improvement tools.
• Descriptive statistics, predictive models like ARIMA for forecasting the prices and GARCH for forecasting variance to know the price volatility.
• Open Source Frameworks: Apache Hadoop, Hive, Spark, TensorFlow, Spark Mllib.
• Experimented and applied various Data science algorithms like regression, classification, KNN and clustering to create decide and create models for solving various business requirements.
• Will demonstrate cross-functional resource interaction to accomplish your goals.
• Experience with deep learning LSTM and RNN based speech recognition using TensorFlow.
• Analyse a large amount of data classify data.
• Visualize data using D3.js.
• Create a model for forecast revenue.
• Performed data analysis by using Hive to retrieve the data from Hadoop cluster, Sql to retrieve data from Oracle database and used Power BI.
• MLperformance a deep analysis of the HTPD/RTPD/LTPD test data to define a model of FBC growth rateacross the temperature.
• MLmodels for projection pre-production SLC, MLC, TLC single and multi-die packages ICC memory.
• Used TensorFlowlibrary in dual GPU environment for training and testing of the Neural Networks
• Distributed Tensorflow on YARN and Kubernetes.
• Develop project requirements and deliverable timelines; execute efficiently to meet the plan timelines.
• Creating and supporting a data management workflow from data collection, storage, and analysis to training and validation.
• Predict future sales value and volume of a brand/item using ARIMA model in SAS/R.
• Develop necessary connectors to plug ML software into wider data pipeline architectures.
• Creating andsupporting a data management workflow from data collection, storage, and analysis to training and validation.
• Identify and assess available machine learning and statistical analysis libraries (including regressors, classifiers, statistical tests, and clustering algorithms).
• Worked Hands on with ETL process.
• Design and build scalable software architecture to enable real-time / big-data processing.
• Acquire business knowledge in the Firm’s risk management processes.
• Be very passionate about quality and have a strong sense of ownership of the work accomplished.
• Be quick to learn new technologies as well as deliver on them in short order.
• Taking responsibility for technical problem solving, creatively meeting product objectives and developing best practices.
• Have a high sense of urgency to deliver projects as well as troubleshoot and fix data queries/ issues.
• Work independently with R&D partners to understand requirements.

Environment: R 9.0, R Studio, Machine learning, Informatic a 9.0, Scala, Spark, Power BI, DL4J, ND4J, Ml, DL,Scikit-learn, Shogun, Accord Framework/AForge.net, Mahout, Data Warehouse,MLlib, H2O, Cloudera Oryx, GoLearn, Apache.

Confidential, BIRMINGHAM, AI

Machine Learning/Data Scientist

Responsibilities:

• Built an IEbot for automating KYC extraction for Institutional entities and Risk& Compliance domain.
• Implementation and design of the patented algorithm for signature less intrusion detection and prevention for SIPtraffic in Siberia's first IDS/IPS product line.
• Ana moly detection using MultivariateGaussian model for traffic optimization
• ACL implementation using TACACS Authentication adapter, OpenSSHcustomization, and PAMmodule implementation.
• Implementation of Character Recognition using Support vectormachinefor performance optimization.
• Worked on Amazon Web Services ( EC2, ELB, VPC, S3, CloudFront, IAM, RDS, Route 53, CloudWatch, SNS,).
• Image compression and reconstruction using Principle component analysis.
• Market Mix Modelling: Helped a leading Sanitary napkin brand in India to identify drivers of sales and distribution across key states through MMM.
• Recommender system using low-rank matrix factorization to increase CTR for add network.
• Collaborate with distributed cross-functional teams on common goals.
• Innovate and leverage machine learning, data mining and statistical techniques to create new, scalable solutions for business problems.
• Optimisation of statistical analysis and forecasting using Lasso, Cross Validation, Random forest, Log regression and prediction Tree basedMLmodels with in R for diabetes incidences on patient cohorts.
• Experience with deep learning LSTM and RNN based speech recognition using TensorFlow.
• Analysea large amount of data classify data.
• Visualize data using D3.js.
• Createa model for forecast revenue.
• Used TensorFlowlibrary in dual GPU environment for training and testing of the Neural Networks
• Co-authored two manuscripts; they are under review for two high impact journals.
• Addressed spend optimization complexities using coefficients of Market Mix exercise.
• Machinelearningautomatically scores user assignment based on few manually scored assignments.
• Developed Online Slot booking system for Assessment test.
• Developing new products in the site with client's specification and solving the issues in the Freshersworld.com site.
• Adding Google analytics code in site.
• Testing the compatibility and functionality of websites in differentbrowsers and mobile.
• DB design and Maintenance.
• Extracted Statistics forperformance metrics analysisfor various components on load testing.
• Applied association rule mining & chain model to identify hidden patterns and rules in remedy ticket analysis which aid in decision making.
• Segmenting ABO population and developing demographic profile against each fragment.
• Isolating customer behavioural patterns by analysing millions of customerdatarecords overa period of time and correlating multiple customers’ attributes.
• Worked on various strategic projects (Customer engagement, SAclosures, Locker surrender etc.) &AdhocproactiveAnalysis with product teams to provide insights and trends using SAS&Excel.

Environment: Apache, Spark MLlib, TensorFlow, Oryx 2, Accord.NET, Amazon Machine Learning (AML)Python, Django, Flask, Tensor Flow, ORM, Jinja 2, Mako, Naive Bayes, SVM,K- means, ANN, Regression.

Confidential, DALLAS, TX

Machine Learning/Data Scientist

Responsibilities:

• Developing and scaling REST APIs and Good understanding and working experience in JSON, JSON Schema, and REST API.
• Object-Oriented Design using common design patterns / Software Debugging, Test-driven development, UML, SVN.
• Created Machine Learning and statistical methods, (SVM, CRF, HMM, sequential tagging) or willingness to intensely learn.
• Used data mining algorithms and approach.
• Developed using Python unit test framework, or any other unit test framework.
• Using Python and Productionizing end-to-end systems.
• Worked on file systems, server architectures, databases, SQL, and data movement (ETL).
• Exposure to python and python packages.
• Collaborate with Risk Analytics teams; Stress Testingteam, Middle Office, IT and other departments.
• Be responsible for creation and execution of test plans, protocols, and documentation.
• Develop and implement innovative AI and machine learning tools that will be used in the Risk.
• Be very passionate about quality and have a keen sense of ownership of the work accomplished.
• Acquire business knowledge in the Firm’s risk management processes.
• Be responsible for creation and execution of test plans, protocols, and documentation.
• Formulate and test hypotheses, extract signals from petabyte scale, unstructured data sets, and ensure that our display advertising business delivers the highest standards of performance.
• Understanding the trade-offs between competing approaches and identifying the ones that are likely to havea real impact on theproduct.
• Lead a project team of systems engineers (HW, FW & SW) and internal and outsourced development partners to develop reliable, cost effective and high-quality solutions.
• Identify and assess available machine learning and statistical analysis libraries (including regressors, classifiers, statistical tests, and clustering algorithms).
• NLP engineer witha profound interest in research and development for cutting edge machine learning techniques.
• Architecture and Design of reusable server components for the web as well as Mobile applications.

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

Confidential, MINNEAPOLIS, MN

Machine Learning

Responsibilities:

• Developing propensity models for Retail liability products to drive proactive campaigns.
• Extraction and tabulation ofdatafrom multipledatasources using R, SAS.
• Datacleansing, transformation and creating new variables using R.
• Built predictive scorecards for Cross-sellingCarolan, Life Insurance, TD, and RD.
• Scoring predictive models as per regulatory requirements & ensuring deliverables with PSI.
• Using Statistical techniques on a need basis ranging from simple significance test to Regression Segmentation techniques for delivering analyses and building strategies.
• Datamodelling and formulation of statistical equations using advanced statistical forecasting techniques.
• Provide guidance and mentoring to team members.
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
• Formulate and test hypotheses, extract signals from petabyte scale, unstructured data sets, and ensure that our display advertising business delivers the highest standards of performance.
• Lead a multi-functional project team.
• Develop necessary connectors to plug ML software into wider data pipeline architectures.
• Applied association rule mining &chain model to identify hidden patterns and rules in remedy ticket analysis which aid in decision making.
• Understanding the client business problems and analysing thedataby using appropriate Statistical models to generate insights.
• Integrated Teradata with R for BI platform and also implemented corporate business rules.

Environment: R Studio, Machine learning, Informatic a 9.0, Scala, Amazon Machine Learning (AML)Python, Django, SAAS.

Confidential

Data Architect/Data Modeler

Responsibilities:

• Worked as DataExpert on a data mining ETL development project using SAS Enterprise Guide.
• Created test plan documents for all back-end database modules.
• Worked with large amounts of structured and unstructured data.
• Responsible for data collection, cleansing, andANOVA. Designed technical solution roadmap to deal with noise in sales data.
• Worked on loading the data from MySQL to HBase where necessary using Scoop.
• Handled end-to-end project from data discovery to model deployment
• Knowledge in Business Intelligence tools and visualization tools such as BusinessObjects, Tableau, ChartIO, etc.
• Knowledge in Machine Learning concepts (GeneralizedLinear models, Regularization, RandomForest, TimeSeries models, etc.).
• Deployed GUI pages by using JSP, JSTL, HTML, DHTML, XHTML, CSS, JavaScript, and 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.
• Monitoring the automated loading processes.
• Communicated with other Health Care info by using Web Services with the help of SOAP, WSDLJAX-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.
• 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.
• 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.
• It was a part of the complete life cycle of the project from the requirements to the production support.
• Implemented the project in Linux environment.

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

Responsibilities:

• Implementation of Metadata Repository, Maintaining Data Quality, Data Clean-up procedures, Transformations, Data Standards, DataGovernanceprogram, Scripts, Stored Procedures, triggers and execution of test plans.
• Developed Internet traffic scoring platform for ad networks, advertisers, and publishers (rule engine, site scoring, keyword scoring, lift measurement, linkage analysis).
• Responsible for communication and negotiation with project related aspects of project loading, construction budget, design alterations, and unexpected events on the project.
• Responsible for defining the key identifiers for each mapping/interface.
• Clients include eBay, Click Forensics, Cars.com, Turn.com, Microsoft, and Look smart.
• Designed the architecture for one of the first analytics 3.0. Online platforms: all-purpose scoring, with on-demand, SaaS, API services.
• Web crawling and text mining techniques to score referral domains, generate keyword taxonomies and assess commercial value of bid keywords.
• Used RAD as Development IDE for web applications.
• 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.
• Performed data quality in TalentOpenStudio.
• 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.