Ramanjaneyulu Reddy

BayapuReddy L.

Email: add5rc@r.postjobfree.com Ph: 980-***-****

Charlotte, NC-28262

EDUCATION

University of North Carolina at Charlotte May 2020 Master of Science: Computer Science.

Jawaharlal Nehru Technological University, Anantapur, India May 2015 Bachelor of Technology: Computer Science.

SKILL HIGHLIGHTS

Languages & scripting: Java, SQL, PLSQL, UNIX Shell Scripting, Scala (basic), HTML (basic).

Hadoop: MapReduce, HIVE, Impala, Apache Spark, SQOOP.

Database: Oracle, MYSQL.

Java Frameworks: Spring, Hibernate, Restful webservices.

Versioning: SVN, GitHub, Bit Bucket.

Job Scheduling. Autosys.

SDLC: Agile Methodology and Waterfall Methodology. WORK EXPERIENCE

Java and Hadoop Developer, Tata Consultancy Services(TCS), Hyderabad, India(3.5 years) Jun 2015 - Dec 2018

Designed and developed high volume data processing middleware system using Apache Spark, HIVE, Impala, Unix Shell Scripting, Autosys to process, analyze financial data by following Agile methodology as software development life cycle for Fraud prevention.

Worked in performing enhancements to an application dealing with Fraud prevention by analyzing customer claims data using Apache Crunch, HIVE, Impala, Unix Shell Scripting and Autosys.

Experience in writing shell scripts to trigger apache Spark jobs and MapReduce jobs.

Developed Restful web services using Spring Framework and maven, designed and developed Batch jobs using Autosys.

Proven track in delivering Release Bundles without post-production defects within committed deadlines.

Extensive experience in maintaining Bitbucket/SVN branches during Project Development. PROJECTS

Telecom Customer Churn Prediction – (Academic) University Of North Carolina Jan 2020 - May 2020 Technology: Apache Spark, Scala, HIVE, Apache Maven.

Developed a tool that will predict telecom customers churn based on several features by using Naïve Bayes model.

Used Spark MLlib library for building Machine learning model for prediction and Spark SQL library for analyzing and transforming the data.

Stored the Prediction data and intermediate filtered data in HIVE tables for querying and analytics purpose. Referral for Investigation – Bank of America July 2016 - Dec 2018 Technology: Apache Spark, Apache Crunch, HIVE, Impala, Unix Shell scripting, Autosys, Apache Maven. Methodology: Agile Methodology.

Developed a Fraud prevention tool, that will monitor the claims requested by customers and figure out the potential fraudulent claims by running several business rules and refer the fraudulent claims to Crimes Corporation Agency, an investigation Agency.

Developed the System to integrate the claims data across 13 different source systems like credit card claims system, Mortgage claims System, Debit card claims system etc. to aggregate the claims made by customers across different systems.

Developed the System to integrate the claims data across 13 different source systems like credit card claims system, Mortgage claims System, Debit card claims system etc. to aggregate the claims made by customers across different systems.

Developed shell scripts to trigger apache Spark jobs and MapReduce jobs.

Scheduled the jobs using Autosys job scheduler.

Validated all the functionalities on the backend by running queries on HIVE and Impala engines.

Developed project in Agile Methodology and has done enhancements in incremental approach in terms of sprints.

Converted the Legacy application built in Apache Crunch to Apache Spark to achieve better performance and provide business analysts more time to do analytics on fraudulent data.

Extensively worked with testing teams to deliver the defect-free code for deployment. Fraud Analytics for Sales Fulfilment Transaction – Bank of America Jun 2015 - Jun 2016 Technology: Core Java, Spring, Hibernate, shell scripting, SQL, PL/SQL, Restful webservices, maven Methodology: Waterfall Model.

The goal of this project is to expose a web service that facilitates the customer facing application which accepts online forms for opening a new account to detect any possible fraudulent activity.

Persisted hot fraudulent data that the application receives every Sign day at a scheduled time to Oracle database and Exposed a web service that takes in a customer application and estimates the risk of fraud.

Developed PL/SQL stored procedures to access data from Oracle database.

Validated all the functionalities on the backend using complex SQL queries.

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