Varshini Ganesh

Implemented machine learning models for predictive analytics, improving detection accuracy

Collaborated with cybersecurity teams to integrate data analytics solutions into existing security infrastructure.

Analyzed data collected from traffic logs using Python and SQL to identify patterns and anomalies.

Assisted in identifying trends and anomalies in network traffic data.

Conducted statistical analysis to evaluate the effectiveness of security measures.

Developed automated scripts in Python for data cleansing and preprocessing.

Presented findings and recommendations to management based on data-driven insights.

Food Order & Delivery Website (Security software project )

• Technology:
• CD: Git, SVN, Docker, Kubernetees,
• Python, Data Analytics, Docker, Sonarqube, DDOS, API security, Rate limiting, Web performance
• Contributions: worked on the project to create a complete solution for safeguarding their websites and setting up their payments
• Created ML detection techniques to find fraud and aid users in maintaining a website without any downtime
• Created several models to track brute force approaches, worked on captcha problems and rate limitation for clients
• Created and implemented a detection system for ATO attacks and credential stuffing specialized in developing robust and secure authentication systems and rate limiting APIs.
• Following best practices of secure coding and OSWAP top 10
• Good knowledge in API security and API top 10 vulnerabilities

Visualization and data collection using Python Pandas:

Developed a dashboard showcasing product sales using python and data visualization library matplotlib.

Machine Learning

• The solution improves brand value and optimizes cash-to-cash cycles for providers of sustainable, organic food products
• Technology:Bluemix, Watson Studio, SPSS modeling, Blockchain, db2, Hyperledger, Machine Learning Node.js, Angular2, Cloudant
• Contribution: Developer, responsible for designing and developing machine learning predictive models using SPSS modeler flows using various ML algorrithms like random forest, C5 driving predictions greatly helping the user to get useful insights from past data
• Developed models that were built on IBM Watson in AWS Sagemaker using Python notebooks

• Worked for various e-commerce clients using WebSphere Commerce Server Technology. Taken part in various customizations in the registration module, administration console, redesign of cart page using widget architecture.
• Delivered good quality code following standards and helped in maintenance of various projects fixing production issues on time.

• WebSphere Commerce Site for leading hardware store
• Technology: WebSphere Commerce 7, Dojo, jQuery, IBM RAD 8.0, db2
• Contribution: Developer, responsible for development of various features which involved creating controller commands, schedulers and general storefront JSP customizations.

• Developed intranet sites using ASP.net and C#

• Worked on storage applications and their performance