Buidler Application: David Li (Bro Duck)

Self-introduction and your profession I have over 3 years of work experience in web3 technologies, including decentralized applications (dApps) and blockchain development. In addition, I have more than 5 years of experience as a data scientist, with a strong background in working with a variety of data sources and tools, as well as statistical and machine learning methods, to solve problems and extract insights from data.

Your Web3 Experiences I have over 3 years of experience working with Solidity and more than 5 years of experience with languages such as C++, Rust, Go, Python, and JavaScript/TypeScript. My work experience includes building and optimizing smart contracts for lending pools and DEX swaps, as well as optimizing gas usage. I have also gained experience in using test frameworks and unit testing methodologies, and have worked with the Cosmos SDK, CosmWasm, and Tendermint Core. I have a strong interest in topics such as proof-of-stake, consensus algorithms, decentralized exchanges, and public-key cryptography.

What would you like to gain from the LXDAO community? There are many potential benefits we can gain from the LXDAO. For example, LXDAO can allow for more efficient decision-making, as they can use smart contracts to automate processes and reduce the need for human intervention. LXDAO also allow for greater transparency and accountability, as all actions and decisions are recorded on the blockchain and can be audited by anyone. Additionally, LXDAO can provide a new way for people to collaborate and work together on projects and initiatives, regardless of their location or other factors.

What would you like to bring to the LXDAO community? As a data scientist, I can bring a wide range of skills and expertise to the LXDAO. For example, I can contribute my knowledge of statistical and machine learning methods, my ability to analyze and interpret large and complex datasets, and my experience with data visualization and communication. I can also take on specific tasks and responsibilities such as collecting, cleaning, and analyzing data, building and evaluating machine learning models, and communicating my findings to stakeholders. Through my work, I can help provide data-driven solutions to problems facing the LXDAO, such as improving efficiency, automating processes, and making informed decisions.