Paola Pilla
About Candidate
Full Stack Web3 Engineer with a strong foundation in blockchain technologies, front-end development, and machine learning. Successfully launched products in high-performance environments, demonstrating proactive leadership and collaboration across teams. Seeking to apply my extensive experience in Web3 to new and innovative projects.
Education
Experiences
● Integrated data from different blockchains and developed a custom blockchain API for enhanced adaptability. ● Proactively took on additional responsibilities beyond designated tasks such as UI/UX. ● Played a key role in the successful launch of a new product in under 6 months, utilizing a new tech stack. ● Collaborated with Executives, Design, and Blockchain teams to deliver user-facing products. ● Engineered efficient front-end systems to support complex UIs integrating with Ethereum and Solana blockchains. ● Conducted code reviews, shared best practices, and engaged in pair-programming sessions. ● Stack: Typescript, React, Tailwind CSS, GraphQL, The Graph, Ethers, WAGMI, Supabase, Vercel, Next.js.
● Developed and maintained the front-end for seven websites using HTML, CSS, Javascript, and React. ● Designed user interfaces for nine websites using Adobe Xd and Figma. ● Increased Casiere's website traffic by over 80% from the first month of redesign and development. ● Stack: HTML, CSS, Solidity, Javascript, React, Webflow.
● Inserted Kapital's products into five of Brazil's most recognized furniture stores within the first year. ● Raised funding and sponsorship from a renowned Brazilian manufacturing company. ● Achieved a positive net profit every year since founding.
● Developed a machine learning program to detect phishing or fraudulent websites with 98% accuracy using Python and MySQL. ● Improved feature engineering using Python's Django and Flask.
● Developed a machine learning program that automatically detects phishing websites with 99% accuracy using Python, Scikit-learn, Django, and Flask. ● Increased efficiency of the takedown team by prioritizing phishing websites detected by the program.