Sriram Venkatesh

Master's

Management Information Systems

Management

NTT DATA GDS

Digital Technology Junior Analyst

- Developed a smart card solution for Australian public transport utilizing the Hortonworks Data Platform (HDP), effectively handling over 10 - Revamped an innovative open-loop payment system, leveraging Big Data within HDP, resulting in a 40% increase in closed-loop payments - Implemented Apache NiFi for efficient processing of smart card device data, seamlessly sending data to Apache Storm from Kafka topics using - Java and Scala, resulting in a 10% increase in data processing efficiency - Architected Apache Storm topologies for orchestrating the processing of diverse device data through stream processing, while leveraging Apache - Spark for batch processing and real-time payment analysis, resulting in a 30% improvement in data processing efficacy - Designed and implemented ETL pipelines to efficiently store and manage data in Hbase & Hive, optimizing data processing and retrieval - Automated report generation, reducing manual effort and streamlining maintenance processes within the Device Management System, resulting in an impressive 30% reduction in operational time and resources - Enhanced a COVID-19 prediction algorithm using Scala and Python, crafted Spark units for real-time analysis, producing a 20% boost in predictive accuracy. Facilitated data-driven decision-making amid challenging circumstances - Leveraged ReactJS, PowerBI, and Python - Pandas, Scikit-Learn, TensorFlow) for travel pattern analysis. Proposed public transport adjustments - Projects - Environment Dashboard - Workplace - Devised a secure Angular-Spring application for storing credentials, implementing robust security measures and layers of privacy, and employing - Designed the backend, incorporating CRUD API calls for seamless integration with the front end while utilizing technologies such as Postman - Node.js, and Angular to further bolster data privacy and security - Decision Tree-Based Tourism Recommendation System (Undergrad - Created a recommendation system using Python, SQL, and Django, integrating a decision tree machine learning algorithm to optimize solutions - Decision Tree logic - Conducted comprehensive analysis of decision trees' impact on a different recommendation engine, resulting in a 35% increase in personalized - Customer Segmentation and Marketing Optimization System - Leveraged Talend for optimized data extraction, improving end-to-end workflow efficiency by 30 - Utilized Alteryx for automated workflows, reducing processing time by 25%, and applied R for advanced statistical analysis, achieving a 20 - Financial Fraud Detection System - Architected a cloud-based financial fraud detection system using Scala and Apache Spark, with Hadoop for efficient large-scale data processing - Integrated Tableau for dynamic data visualization, enhancing fraud analysis capabilities - Implemented a real-time monitoring mechanism using Kafka, detecting transaction anomalies instantly - Orchestrated the migration and scaling of the system to a Software as a Service (SaaS) platform, leveraging Docker for streamlined deployment