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Data Scientist/machine Learning Engineer Resume

Columbus, OH

SUMMARY:

  • Around 8 year’ s of hands on experience and comprehensive industry knowledge of Machine Learning, Statistical Modeling, Data Analytics, Data Modeling, Data Architecture, Data Analysis, Data Mining, Text Mining & Natural Language Processing (NLP), Artificial Intelligence algorithms, Business Intelligence, Analytics Models (like Decision Trees, Linear & Logistic Regression, Hadoop (Hive, PIG), R, Python, Spark, Scala, MS Excel, SQL and Postgre SQL, Erwin.
  • Strong knowledge in all phases of the SDLC (Software Development Life Cycle) from analysis, design, development, testing, implementation and maintenance.
  • Experienced in Data Modeling techniques employing Data warehousing concepts like star/snowflake schema and Extended Star.
  • Good exposure on Tableau Desktop & Server, R - Language, Python, ElasticSearch, Blockchain, Hyperledger, IBM Blockchain, Talend, Apache Spark, IBM Watson, and PowerBI.
  • Expertise in applying data mining techniques and optimization techniques in B2B and B2C industries.
  • Expertise in writing functional specifications, translating business requirements to technical specifications, created/maintained/modified database design document with detailed description of logical entities and physical tables.
  • Excellent knowledge of Machine Learning, Mathematical Modeling and Operations Research. Comfortable with R, Python, SAS and Weka, MATLAB, Relational databases. Deep understanding & exposure of Big Data Eco-system.
  • Expertise in Data Analysis, Data Migration, Data Profiling, Data Cleansing, Transformation, Integration, Data Import, and Data Export through the use of multiple ETL tools such as Informatica Power Center.
  • Proficient in Machine Learning, Data/Text Mining, Statistical Analysis & Predictive Modeling.
  • Expertise in data acquisition, storage, analysis, integration, predictive modeling, logistic regression, decision trees, data mining methods, forecasting, factor analysis, cluster analysis, Anova and other advanced statistical techniques.
  • Excellent knowledge and experience in OLTP/OLAP System Study with focus on Oracle Hyperion Suite of technology, developing Database Schemas like Star schema and Snowflake schema (Fact Tables, Dimension Tables) used in relational, dimensional and multidimensional modeling, physical and logical Data modeling using Erwin tool,
  • Experienced in building data models using Machine Learning techniques for Classification, Regression, Clustering and Associative mining.
  • Extensive experience in stacks like SSRS, SSIS, SSAS.
  • Expert in creating PL/SQL Schema objects like Packages, Procedures, Functions, Subprograms, Triggers, Views, Materialized Views, Indexes, Constraints, Sequences, Exception Handling, Dynamic SQL/Cursors, Native Compilation, Collection Types, Record Type, Object Type using SQL Developer.
  • Working experience in Hadoop ecosystem and Apache Spark framework such as HDFS, Map Reduce, HiveQL, SparkSQL, PySpark.
  • Very good experience and knowledge in provisioning virtual clusters under AWS cloud which includes services like EC2, S3, and EMR.
  • Proficient in data visualization tools such as Tableau, Python Matplotlib, R Shiny to create visually powerful and actionable interactive reports and dashboards.
  • Excellent Tableau Developer, expertise in building, publishing customized interactive reports and dashboards with customized parameters and user-filters using Tableau (9.x/10.x)
  • Experienced in Agile methodology and SCRUM process.
  • Strong business sense and abilities to communicate data insights to both technical and nontechnical clients.

TECHNICAL SKILLS:

Big Data Technologies: Hadoop, Hive, HDFS, MapReduce, Pig, Kafka.

Machine Learning: Regression, Polynomial Regression, Random Forest, Logistic Regression, Decision Trees, Classification, Clustering, Association, Simple/Multiple linear, Kernel SVM, K-Nearest Neighbours (K-NN).

OLAP/ BI / ETL Tool: Business Objects 6.1/XI, MS SQL Server 2008/2005 Analysis Services (MS OLAP, SSAS), Integration Services (SSIS), Reporting Services (SSRS), Performance Point Server (PPS), Oracle 9i OLAP, MS Office Web Components (OWC11), DTS, MDX, Crystal Reports 10, Crystal Enterprise 10(CMC)

BI Tools: Tableau, Tableau server, Tableau Reader, SAP Business Objects, OBIEE, QlikView, SAP Business Intelligence, Amazon Redshift, or Azure Data Warehouse

Packages: ggplot2, caret, dplyr, Rweka, gmodels, RCurl, tm, C50, twitter, NLP, Reshape2, rjson, plyr, pandas, numPy, seaborn, sciPy, matplot lib, scikit-learn, Beautiful Soup, Rpy2, sqlalchemy.

Web Technologies: JDBC, HTML5, DHTML and XML, CSS3, Web Services, WSDLTools

Erwin r 9.6, 9.5, 9.1, 8.x, Rational Rose, ER/Studio, MS Visio, SAP Power designer.

Languages: Java 8, Python, R

Databases: SQL, Hive, Impala, Pig, Spark SQL, Databases SQL-Server, MySQL, MS Access, HDFS, HBase, Teradata, Netezza, Mongo DB, Cassandra, SAP HANA.

Reporting Tools: MS Office (Word/Excel/Power Point/ Visio), Tableau, Crystal reports XI, Business Intelligence, SSRS, Business Objects 5.x/ 6.x, Cognos7.0/6.0.

ETL Tools: Informatica Power Centre, SSIS.

Version Control Tools: SVM, GitHub.

Methodologies: Ralph Kimball and Bill Inmon data warehousing methodology, Rational Unified Process (RUP), Rapid Application Development (RAD), Joint Application Development (JAD).

Operating System: Windows, Linux, Unix, Macintosh HD, Red Hat.

PROFESSIONAL EXPERIENCE:

Confidential, Columbus, OH

Data Scientist/Machine Learning Engineer

Roles & Responsibilities:

  • Worked with several R packages including knitr, dplyr, SparkR, CausalInfer, Space-Time.
  • Coded R functions to interface with CaffeDeepLearningFramework.
  • Used Pandas, Numpy, Seaborn, Scipy, Matplotlib, Sci-kit-learn, and NLTK in Python for developing various machinelearning algorithms.
  • Installed and used CaffeDeep Learning Framework
  • Worked on different data formats such as JSON, XML and performed machine learning algorithms in Python.
  • Setup storage and data analysis tools in Amazon Web Services (AWS) cloud computing infrastructure.
  • Implemented end-to-end systems for Data Analytics, Data Automation and integrated with custom visualization tools using R, Mahout, Hadoop and Mongo DB.
  • Worked as DataArchitects and IT Architects to understand the movement of data and its storage and ER Studio 9.7.
  • Utilized Spark, Scala, Hadoop, HBase, Cassandra, MongoDB, Kafka, Spark Streaming, MLLib, Python, a broad variety of machine learning methods including classifications, regressions, dimensionally reduction etc. and Utilized the engine to increase user lifetime by 45% and triple user conversations for target categories.
  • Used Spark Data frames, Spark-SQL, Spark MLLib extensively and developing and designing POC's using Scala, Spark SQL and MLlib libraries.
  • Used Data Quality Validation techniques to validate Critical Data Elements (CDE) and identified various anomalies.
  • Extensively worked on Data Modeling tools Erwin Data Modeler to design the Data Models.
  • Developed various Qlik-View Data Models by extracting and using the data from various sources files, DB2, Excel, Flat Files and Big data.
  • Participated in all phases of Data-Mining, Data-collection, Data-Cleaning, Developing-Models, Validation, Visualization and Performed Gap Analysis.
  • Data Manipulation and Aggregation froma different source using Nexus, Toad, Business Objects, PowerBI and SmartView.
  • Implemented Agile Methodology for building an internal application.
  • Focus on integration overlap and Informatica newer commitment to MDM with the acquisition of Identity Systems.
  • Good knowledge of Hadoop Architecture and various components such as HDFS, JobTracker, Task Tracker, Name Node, Data Node, SecondaryNameNode, and MapReduce concepts.
  • As Architect delivered various complex OLAP Databases/Cubes, Scorecards, Dashboards and Reports.
  • Programmed a utility in Python that used multiple packages (Scipy, Numpy, Pandas)
  • Implemented Classification using supervised algorithms like Logistic Regression, Decision trees, KNN, Naive Bayes.
  • Designed both 3NF data models for ODS, OLTP systems and Dimensional DataModels using Star and Snow flake Schemas.
  • Updated Python scripts to match training data with our database stored in AWS Cloud Search, so that we would be able to assign each document a response label for further classification.
  • Created SQL tables with referential integrity and developed queries using SQL, SQL PLUS and PL/SQL.
  • Designed and developed Use Case, Activity Diagrams, Sequence Diagrams, OOD (Object oriented Design) using UML and Visio.
  • Interaction with BusinessAnalyst, SMEs and other DataArchitects to understand Business needs and functionality for various project solutions
  • Interaction with BusinessAnalyst, SMEs, and other DataArchitects to understand Business needs and functionality for various project solutions
  • Identifying and executing process improvements, hands-on in various technologies such as Oracle, Informatica, and BusinessObjects.

Environment: AWS, R, Informatica, Python, HDFS, ODS, OLTP, Oracle 10g, Hive, OLAP, DB2, Metadata, MS Excel, Mainframes MS Vision, Map-Reduce, Rational Rose, SQL, and MongoDB.

Confidential, San Antonio, TX

Data Scientist

Roles & Responsibilities:

  • Extracted data from HDFS and prepared data for exploratory analysis using data munging
  • Built models using Statistical techniques like Bayesian HMM and Machine Learning classification models like XGBoost, SVM, and Random Forest.
  • Participated in all phases of data mining, data cleaning, data collection, developing models, validation, visualization, and performed Gap analysis.
  • A highly immersive Data Science program involving Data Manipulation&Visualization, Web Scraping, Machine Learning, Python programming, SQL, GIT, MongoDB, Hadoop.
  • Setup storage and data analysis tools in AWS cloud computing infrastructure.
  • Installed and used Caffe Deep Learning Framework
  • Worked on different data formats such as JSON, XML and performed machine learning algorithms in Python.
  • Worked as Data Architects and IT Architects to understand the movement of data and its storage and ER Studio 9.7.
  • Developing Models on scala and Spark for users, prediction models, sequential algorithms
  • Used pandas, numpy, seaborn, matplotlib, scikit-learn, scipy, NLTK in Python for developing various machine learning algorithms.
  • Data Manipulation and Aggregation from different source using Nexus, Business Objects, Toad, Power BI and Smart View.
  • Implemented Agile Methodology for building an internal application.
  • Focus on integration overlap and Informatica newer commitment to MDM with the acquisition of Identity Systems.
  • Coded proprietary packages to analyze and visualize SPCfile data to identify bad spectra and samples to reduce unnecessary procedures and costs.
  • Programmed a utility in Python that used multiple packages (numpy, scipy, pandas)
  • Implemented Classification using supervised algorithms like Logistic Regression, Decision trees, Naive Bayes, KNN.
  • As Architect delivered various complex OLAPdatabases/cubes, scorecards, dashboards and reports.
  • Updated Python scripts to match training data with our database stored in AWS Cloud Search, so that we would be able to assign each document a response label for further classification.
  • Used Teradata utilities such as Fast Export, MLOAD for handling various tasks data migration/ETL from OLTP Source Systems to OLAP Target Systems
  • Data transformation from various resources, data organization, features extraction from raw and stored.
  • Validated the machine learning classifiers using ROC Curves and Lift Charts.

Environment: Unix, Python 3.5.2, MLLib, SAS, regression, logistic regression, Hadoop 2.7.4, NoSQL, Teradata, OLTP, random forest, OLAP, HDFS, ODS, NLTK, SVM, JSON, XML and MapReduce.

Confidential, Dallas, TX

Data Scientist/R Developer

Roles & Responsibilities:

  • Designed an Industry standard data Model specific to the company with group insurance offerings, Translated the business requirements into detailed production level using Workflow Diagrams, Sequence Diagrams, Activity Diagrams and Use Case Modeling
  • Involved in design and development of data warehouse environment, liaison to business users and technical teams gathering requirement specification documents and presenting and identifying data sources, targets and report generation.
  • Recommend and evaluate marketing approaches based on quality analytics of customer consuming behavior.
  • Determine customer satisfaction and help enhance customer experience using NLP.
  • Work on Text Analytics, Naive Bayes, Sentiment analysis, creating word clouds and retrieving data from Twitter and other social networking platforms.
  • Conceptualized the most-used product module (Research Center) after building a business case for approval, gathering requirements and designing the User Interface
  • A team member of Analytical Group and assisted in designing and development of statistical models for the end clients. Coordinated with end users for designing and implementation of e-commerce analytics solutions as per project proposals.
  • Conducted market research for client; developed and designed sampling methodologies, and analyzed the survey data for pricing and availability of clients' products. Investigated product feasibility by performing analyses that include market sizing, competitive analysis and positioning.
  • Successfully optimized codes in Python to solve a variety of purposes in data mining and machine learning in Python.
  • Facilitated stakeholder meetings and sprint reviews to drive project completion.
  • Successfully managed projects using Agile development methodology
  • Project experience in Data mining, segmentation analysis, business forecasting and association rule mining using Large Data Sets with Machine Learning.
  • Automated Diagnosis of Blood Loss during Accidents and Applied Machine Learning algorithms to diagnose blood loss from vital signs (ECG, HF, GSR, etc.) . Demonstrated performances of 94.6% on par with state-of-the-art models used in industry.

Environment: R, MATLAB, MongoDB, exploratory analysis, feature engineering, K-Means Clustering, Hierarchical Clustering, Machine Learning), Python, Spark (MLlib, PySpark), Tableau, SAS, Tensor Flow, regression, logistic regression, Hadoop 2.7, OLTP, random forest, OLAP, HDFS, ODS, NLTK, SVM, JSON, XML and MapReduce.

Confidential, New York, NY

Data Analyst

Roles & Responsibilities:

  • Data analysis and reporting using MySQL, MS Power Point, MS Access and SQL assistant.
  • Involved in MySQL, MS Power Point, MS Access Database design and design new database on Netezza which will have optimized outcome.
  • Involved in writing T-SQL, working on SSIS, SSRS, SSAS, Data Cleansing, Data Scrubbing and Data Migration.
  • Involved in writing scripts for loading data to target data Warehouse using Bteq, Fast Load, Multiload
  • Create ETL scripts using Regular Expressions and custom tools (Informatica, Pentaho, and Sync Sort) to ETL data.
  • Developed SQL Service Broker to flow and sync of data from MS-I to Microsoft's master database management (MDM).
  • Involved in loading data between Netezza tables using NZSQL utility.
  • Worked on Data modeling using Dimensional Data Modeling, Star Schema/Snow Flake schema, and Fact& Dimensional, Physical & Logical data modeling.
  • Generated Stats pack/AWR reports from Oracle database and analyzed the reports for Oracle wait events, time consuming SQL queries, table space growth, and database growth.

Environment: MySQL, MS Power Point, MS Access, MY SQL, MS Power Point, MS Access, Netezza, DB2, T-SQL, DTS, SSIS, SSRS, SSAS, ETL, Oracle, Star Schema and Snow Flake Schema.

Confidential, Weehawken, NJ

Engineer- Data Analytics

Roles & Responsibilities:

  • 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.
  • 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 Jdbc, JSP, Servlets and EJB 1.1, Web Services, SOAP, WSDL
  • 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.
  • 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
  • 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, HIVE, AWS.

Confidential

Data Analyst

Responsibilities:

  • Worked with internal architects, assisting in the development of current and target state data architectures.
  • Worked with project team representatives to ensure that logical and physical ER/Studio data models were developed in line with corporate standards and guidelines.
  • Involved in defining the business/transformation rules applied for sales and service data.
  • Implementation of Metadata Repository, Transformations, Maintaining DataQuality, DataStandards, DataGovernanceprogram, Scripts, Stored Procedures, triggers and execution of test plans
  • Define the list codes and code conversions between the source systems and the data mart.
  • Involved in defining the source to business rules, target data mappings, data definitions.
  • Responsible for defining the key identifiers for each mapping/interface.
  • Remain knowledgeable in all areas of business operations in order to identify systems needs and requirements.
  • Responsible for defining the key identifiers for each mapping/interface.
  • Performed data quality in Talend Open Studio.
  • Enterprise Metadata Library with any changes or updates.
  • Document data quality and traceability documents for each source interface.
  • Establish standards of procedures.
  • Coordinated meetings with vendors to define requirements and system interaction agreement documentation between client and vendor system.

Environment: Windows Enterprise Server 2000, SSRS, SSIS, Crystal Reports, DTS, SQL Profiler, and Query Analyze.

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