Candidates About

 

Bharath

Machine Learning/Data Scientist

 

PROFESSIONAL SUMMARY:

 

Having 8+ years of experience in Machine Learning, Data mining with large datasets of Structured and Unstructured data, Data Acquisition, Data Validation, Predictive modeling, Data Visualization.

§  Proficient in gathering and analyzing the Business Requirements with experience in documenting System Requirement Specifications (SRS) and Functional Requirement Specifications (FRS).

§  Knowledge for Development, Implementation, and Maintenance of Business Intelligence tools and applications.

§  Extensive experience in Text Analytics, developing different Statistical Machine Learning, DataMining solutions to various business problems and generating data visualizations using R, Pythonand Tableau.

§  Exposed to all phases of software development life cycle SDLC including in-depth knowledge of Agile methodology, Enterprise Reporting Life Cycle, SQL Server Migrations, Change control rules, problem management and escalation procedures.

§  Experience in Extracting data for creating Value Added Datasets using Python, R, SAS, Azure and SQL to analyze the behavior to target a specific set of customers to obtain hidden insights within the data to effectively implement the project Objectives.

§  Experience in creating Data Visualizations for KPI's as per the business requirements for various departments.

§  Experience in using Statistical procedures and Machine Learning algorithms such as ANOVA, Clustering and Regression and Time Series Analysis to analyze data for further Model Building.

§  Designing of Physical Data Architecture of New system engines.

§  Expertise in transforming business requirements into analytical models, designing algorithms, building models, developing DataMining and reporting solutions.

§  Excellent experience in Extract, Transfer and Load process using ETL tools like Data Stage, Informatica, Data Integrator and SSIS for Data migration and Data Warehousing projects.

§  Experienced in Data Integration Validation and Data Quality controls for ETL process and DataWarehousing using MS Visual Studio, SSAS, SSISandSSRS.

§  Capability in scheduling and subscribing extracts, troubleshooting failed refresh activity, monitoring dashboards performance on the reporting server.

§  Highly skilled in using visualization tools like Tableau, ggplot2 and d3.js for creating dashboards.

§  Documenting interface specifications, data warehouse business rules, and transformations even reporting requirements.

§  Highly self-motivated, enthusiastic, and result-driven with the ability to effectively communicate with all levels of the organization including senior management and executives.

§  Guide the development teams to break down large and complex user story into simplified versions for execution.

§  Experienced in Database optimization and developing stored procedures, Triggers, Cursors, Joins, Views, Cursors and SQL on databases: MySQL, Oracle10g, OMWB tool.

§  Created reports for the users using Tableau by connecting to multiple data sources like Flat Files, MS Excel, CSV files, SQL Server, and Oracle.

§  Skilled in Data warehousing tools, Data Mapping, Unit Testing, Migration Conversions and Process Documentation.

§  Exposed to all phases of software development life cycle SDLC including in-depth knowledge of Agile methodology, Enterprise Reporting Life Cycle, SQL Server Migrations, Change control rules, problem management and escalation procedures.

§  Good SQL Server Administration skills including, Backups, Disaster Recovery Model, database maintenance, user authorizations, Database creation, Tables, indexes.

§  Experience in writing T-SQL, working on Data Cleansing, Data Scrubbing and Data Migration, also created Indexed Views, complex Stored Procedures, effective functions, and appropriate Triggers to facilitate efficient data manipulation and data consistency.

 

EDUCATION:

 

Bachelor’s in computer science and Engineer 

               

TECHNICAL SKILLS:

 

Languages	HTML5, DHTML, WSDL, CSS3, C, C++, XML, R/R Studio, SAS Enterprise Guide, SAS, R (Caret, Weka, ggplot), Perl, MATLAB, Mathematica, FORTRAN, DTD, Schemas, JSON, Ajax, Java, Scala,
NO SQL Databases	Cassandra, HBase, MongoDB, MariaDB
Software/Libraries	Keras, Caffe, TensorFlow, OpenCV, Scikit-learn, Pandas, NumPy, Microsoft Visual Studio, Microsoft Office.
Development Tools	Microsoft SQL Studio, IntelliJ, Eclipse, NetBeans.
Machine Learning Algorithms	Neural Networks, Decision trees, Support Vector Machines, Random forest, Convolutional Neural Networks, Logistic Regression, PCA, K- means, KNN.
Development Methodologies	Agile/Scrum, UML, Design Patterns, Waterfall
Reporting Tools	MS Office (Word/Excel/PowerPoint/ Visio/Outlook), Crystal Reports XI, SSRS, Cognos 7.0/6.0.
BI Tools	Microsoft 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

 

 

PROFESSIONAL EXPERIENCE :     

 

 

Description: SITA is a multinational information technology company providing IT and telecommunication services to the air transport industry. The company provides its services to around 400 members and 2,800 customers worldwide which is about 90% of the world's airline business.

 

 

Responsibilities:

§  DevelopedSpark Python modules for machine learning & predictive analytics in Hadoop on AWS. Implemented a Python-based distributed random forest via Python streaming.

§  Implemented Porter Stemmer (Natural Language Tool Kit) and NLP bag of words model (CountVectorizer) to prepare the data. Resulted clusters are plotted visually using Tableau legends.

§  Developed Natural Language Processing to automate the classification of positive and negative reviews by the text processing using NLTK. (Sentimental Analyzer)

§  Extracting data from Big Data Hadoop Data Lake, Excel, Analyzing, Cleaning, Sorting, Merging Reporting and creating dashboards using Base SAS, SAS Macros, SQL, Hive, SAS VA, SAS, and Excel.

§  Conducting studies, rapid plots and using advanced data mining and statistical modeling techniques to build a solution that optimizes the quality and performance of data.

§  Demonstrated experience in design and implementation of Statistical models, Predictive models, enterprise data model, metadata solution and data lifecycle management in both RDBMS, Big Data environments.

§  Implementing Natural Language Processing (NLP) tools such as NLTK, Stanford’s core NLP suite

§  Stored and retrieved data from data-warehouses using Amazon Redshift and designed and implemented system architecture for Amazon EC2 based cloud-hosted solution for the client.

§  Developed Simple to complex Map Reduce Jobs using Hive and Pig and developed multiple MapReduce jobs in java for data cleaning and preprocessing.

§  Analyzing large data sets apply machine learning techniques and develop predictive models, statistical models and developing and enhancing statistical models by leveraging best-in-class modeling techniques.

§  Experience in Implementing python alongside using various libraries such as matplotlib for charts and graphs, MySQL DB for database connectivity, Pandas data frame, NumPy.

§  Responsible for developing predictive models and deploy them with interactive visualizations in Seaborn, matplotlib, Tableau.

§  Create and maintain SSIS packages. Maintain SSRS reports. Utilize SourceTree and Git to maintain version control.

§  Built Random Forest Regression model in R for the time series prediction and connected with tableau using external ODBC in the tableau.

§  Generated interactive Bar Graphs on the forecasted sales through Tableau.

§  Wrangled data, worked on large datasets (acquired data and cleaned the data), analyzed trends by making visualizations using matplotlib and python.

§  Experience with TensorFlow, Theano, Keras and other Deep Learning Frameworks.

§  Built Artificial Neural Network using TensorFlow in Python to identify the customer's probability of canceling the connections. (Churn rate prediction)

§  Understanding the business problems and analyzing the data by using appropriate Statistical models to generate insights.

§  Predicted the products that are prone to be back ordered and products that are expected to be canceled.

§  Implemented Classification using supervised algorithms like Logistic Regression, Decision trees, KNN, Naive Bayes.

§  Designed both 3NF data models for ODS, OLTP systems and Dimensional Data Models using Star and Snowflake 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.

§  Identifying and executing process improvements, hands-on in various technologies such as Oracle, Informatica, and BusinessObjects.

 

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

 

 

 

Description: CBRE Group, Inc. a Fortune 500 and S&P 500 company headquartered in Los Angeles, is the world’s largest commercial real estate services and investment firm (based on 2017 revenue). The company has more than 80,000 employees and serves real estate investors and occupiers through approximately 450 offices (excluding affiliates) worldwide.

 

Responsibilities:

§  Responsible for performing Machine-learning techniques regression/classification to predict the outcomes.

§  Responsible for design and development of advanced R/Python programs to prepare to transform and harmonize data sets in preparation for Modeling.

§  Identifying and executing process improvements, hands-on in various technologies such as Oracle, Informatica, and Business Objects.

§  Implemented SparkMlib utilities such as including classification, regression, clustering, collaborative filtering and dimensionality reduction.

§  Utilized Convolution Neural Networks to implement a machine learning image recognition componentusing TensorFlow.

§  Responsible for design and development of Python programs to prepare transform and harmonize data sets in preparation for Modeling.

§  Handled importing data from various data sources (GOVWIN), performed transformations using Spark, and loaded data into HDFS.

§  Programmed several components for the company's follow up product line, using C#, NUnit, SQLite, git, and WiX.

§  Improve Bag-of-Words features with TF-IDF algorithm, and advanced text and NLP feature-engineering and Machine learning algorithm to process crawled data

§  Interaction with Business Analyst, SMEs and other Data Architects to understand Business needs and functionality for various project solutions.

§  Implemented Back-propagation in generating accurate predictions.

§  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.

§  Handled importing data from various data sources, performed transformations using Hive, Map Reduce, and loaded data into HDFS.

§  Worked on Spark tool collaborating with ML libraries in eliminating a shotgun approach to understand customer buying patterns.

§  Responsible for handling Hive queries using Spark SQL that integrates with Spark environment.

§  Created SQL tables with referential integrity and developed queries using SQL, SQL*PLUSandPL/SQL.

§  Involved with Data Analysis primarily Identifying Data Sets, Source Data, Source Meta Data, Data Definitions and Data Formats

§  Performance tuning of the database, which includes indexes, and optimizing SQL statements, monitoring the server.

§  Used Python and Spark to implement different machine learning algorithms including Generalized Linear Model, SVM, Random Forest, Boosting and Neural Network

§  Independently coded new programs and designed Tables to load and test the program effectively for the given POC's using with Big Data/Hadoop.

§  Wrote simple and advanced SQL queries and scripts to create standard and Adhoc reports for senior managers.

§  Created PL/SQL packages and Database Triggers and developed user procedures and prepared user manuals for the new programs.

§  Participated in Business meetings to understand the business needs & requirements.

Environment: Python, MDM, PL/SQL, Tableau, Git, NLP, SQL Server, MLLib, Scala NLP, SSMS, ERP, CRM, Netezza, Cassandra, SQL, PL/SQL, SSRS, Informatica, Spark, Azure, R Studio, MongoDB, JAVA, HIVE.

 

 

 

 

Description: Broadridge Financial Solutions, Inc. is a US servicing company for the financial industry founded in 2007 as a spin-off from Automatic Data Processing (ADP). The main fields of work are in securities processing, clearingand investor communication.

 

Responsibilities:

§  Generated DDL scripts using Forward Engineering technique to create objects and deploy them into thedatabases.

§  Reverse engineered existing databaseschemas to implement changes and updates for existing tables andviews.

§  Experienced in Designing Database with prominent activities like maintaining sequences, index, and primary key, foreign key, manipulating columns and tables.

§  Translated business requirements into working logical and physical data models for Data warehouse, Data martsandOLAP applications.

§  Developed SQL, BTEQ (Teradata) queries for Extracting data from the production database and built data structures, reports.

§  Performed Data modeling using TOAD Data Modeler. Identified objects and relationships and how those all fit together as logical entities, these are then translated into physical design using forward engineering TOAD Data Modeler tool.

§  Worked with BTEQ to submit SQL statements, import and export data, and generate reports in Teradata.

§  Designed and documented Use Cases, Activity Diagrams, Sequence Diagrams, OOD (Object Oriented Design) using UML and Visio.

§  Responsible for Dimensional Data Modeling and Modeling Diagrams using ERWIN.

§  Designed and implemented a Data Lake to consolidate data from multiple sources, using Hadoop stack technologies like SQOOP, HIVE/HQL.

§  Performed data cleaning and data manipulation activities using NZSQL utility.

§  Excellent knowledge and experience in Technical Design and Documentation.

§  Designed and Developed OraclePL/SQL Procedures and UNIX Shell Scripts for Data Import/Export and Data Conversions.

§  Installing and configuring the 3-node Cluster in AWS EC2 Linux Servers.

§  Performed data cleaning and data manipulation activities using NOSQL utility.

§  Developing the Conceptual Data Models, Logical data models and transformed them into creating the schema using ERWIN.

§  Written complex SQLqueries for validating the data against different kinds of reports

§  In-depth analyses of datathe report was prepared weekly, biweekly, monthly using MS Excel, SQL&UNIX.

§  Performance Tuning (Database Tuning, SQL Tuning, Application/ETL Tuning)

§  Create and alter SQL statements before sending database change request to DBA team.

§  Maintained and documented all create and alter SQL statements for all release.

 

 

Environment: UNIX, Sybase, Business Objects, DB2, SQL Server, PL/SQL, ERWIN, Teradata, Oracle DB2, SQL Server, MS Visio MS Outlook, MS Office Suite, MS Project, MS Excel, MS Word, Windows Server.

 

 

 

Description: Wells Fargo & Company, a diversified financial services company, provides retail, commercial, and corporate banking services to individuals, businesses, and institutions. Its Community Banking segment offers checking, savings, market rate, and individual retirement accounts, as well as time deposits and remittances.

 

Responsibilities:

§  Work with users to identify the most appropriate source of record required to define the asset data for financing

§  Performed data profiling in Target DWH

§  Experience in using OLAP function like Count, SUMand CSUM

§  Performed Data analysis and Data profiling using complex SQL on various sources systems including Oracle and Teradata.

§  Hands on Experience on Sqoop.

§  Developed normalized Logical and Physical database models for designing an OLTP application.

§  Developed new scripts for gathering network and storage inventory data and make Splunk ingest data.

§  Imported the customer data into Python using Pandas libraries and performed various data analysis - found patterns in data which helped in key decisions for the company

§  Created tables in Hive and loaded the structured (resulted from Map Reduce jobs) data

§  Using HiveQL developed many queries and extracted the required information.

§  Exported the data required information to RDBMS using Sqoop to make the data available for the claims processing team to assist in processing a claim based on the data.

§  Design and deploy rich Graphic visualizations with Drill Down and Drop-down menu option and Parameterized using Tableau.

§  Extracted data from the database using SAS/Access, SAS SQL procedures and create SAS data sets.

§  Created Teradata SQL scripts using OLAP functions like RANK () to improve the query performance while pulling the data from large tables.

§  Worked on MongoDB database concepts such as locking, transactions, indexes, Sharding, replication, schema design, etc.

§  Performed Data analysis using Python Pandas.

§  Good experience in Agile Methodologies, Scrum stories, and sprints experience in a Python-based environment, along with data analytics and Excel data extracts.

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