Aishwarya Venkatadri

Hey there! I'm Aish a web development enthusiast and recent grad from Brainstation. I'm all about crafting awesome websites using cool tech like Knex.js, Express.js, Node.js, React.js, and more. From design to deployment, I've got the full stack covered, and I love playing with APIs, making things responsive, and collaborating on GitHub.
Before diving into web development, I spent 6 years in Risk Management, focusing on fraud detection and prevention for e-commerce giants like Shopify and Amazon. I live by the 'succeed or learn' motto and thrive on turning creative ideas into real, impactful websites. I'm on a mission to build a better web, one line of code at a time. Let's chat about how I can bring my passion and skills to your team!

Work Experience:

• Risk Analyst | Shopify
  • January 2022 - 2023, Vancouver, Canada
  • Utilized pattern recognition, root cause analysis, and process review to prevent over 150 cases of fraudulent activity, saving approximately $35,000.
  • Monitored 10,000+ transactions, swiftly identifying and blocking suspicious activities.
  • Collaborated with data science teams to define key performance indicators (KPIs) for data mining and forecast future fraud trends.
• Transaction Risk Analyst | Amazon
  • January 2017 - 2021, Bengaluru, India
  • Analyzed incorrect transfers of customer accounts, leading to a 37% improvement in customer assistance after conducting a root cause analysis and audit report.
  • Trained new hires on Bad Actor Prevention, compromised account revival, and fraud pattern recognition.
  • Conducted quality audits identifying areas of improvement, and establishing high standards for all work.

Education:

• Diploma, Web Development
  • BrainStation, Vancouver, Canada
  • September 2023 - December 2023
• Bachelor in Engineering, Computer Science
  • Visvesvaraya Technological University, Karnataka, India
    • August 2013 - 2017
    • Placed second in a national-level technical paper presentation on "Chatterbot technology using XML" organized by ITSE.
    • Presented a national-level technical paper on "Quantitative radiomics approach for prostate cancer detection" in collaboration with IEEE.
    • Conducted research on decision tree for predicting the purchase habits of the retail customer.