Contributor Proposal
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Title: Luciano Guasco (@luchux) Contributor Proposal, October 1st 2021
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Background:
- I am building this proposal as my first developer contributor proposal after the test period.
- During the test period, I helped in DXvote front end issues, refactoring inline styles into styled components, and created new features for proposals pages.
- I have had a good understanding of how the organization works, the values, the missions, and the responsibilities I am involved in.
- I am building this proposal as my first developer contributor proposal after the test period.
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Timeframe:
- 2.5 months, from October 1st 2021 - December 15th 2021.
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Proposed Scope of Contribution:
- Goals:
- Help with issues and features in DXvote, Omen, and Swapr, focusing on the front end development cycle.
- Help establish a deployment infrastructure for DXvote that involves testing frameworks, to leverage the introduction of new bugs.
- Learn more and contribute as possible in the DXDao Governance Infrastructure; learn and contribute in migration of the app to rollups and side chains (Arbitrum, or any other performance improvements)
- Help onboarding new developer members with the knowledge acquired.
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Responsibilities:
- Adding testing and tests to minimize bugs introduction risk on DXvote.
- Collaborate in the development of the frontend for new proposal creation steps.
- Refactoring unmaintainable code through best practices.
- Fixing issues in the metadata of proposals lists, and proposal detail views.
- Attend and participate in developers and governance meetings.
- Expand my knowledge on Omen and Swapr to allow contribution in the frontend initially.
- Goals:
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Compensation:
- Experience Level: 3
- Time commitment: Full-time for 2.5 months of work at Level 3, to be sent 1.5 months compensation on the first payment proposal and the remaining on the second payment proposal excluding REP. All REP will be claimed on the second payment proposal.
- 2 week trial period (Level 3 at 50%)
- $1,500 DAI
- $1,000 DXD in a vesting contract continuously for two years with a one year cliff
- 0.0417% REP (697.2)
- Month 1 (Level 3 at 80%)
- $4800 DAI
- $3,200 DXD in a vesting contract continuously for two years with a one year cliff
- 0.1333% REP (2,229.92)
- Month 2 (Level 3 at 80%)
- $ 4800 DAI
- $3,200 DXD in a vesting contract continuously for two years with a one year cliff
- 0.1333% REP (2,229.92)
- 2 week trial period (Level 3 at 50%)
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Work Experience:
- Past Work for DXdao
- Research and Development:
- High Performance and Availability Distributed Computing: Development and Outlook: Computación distribuida de alto rendimiento y disponibilidad: desarrollo y perspectiva
- Framework for intruder detection using Defeasible Logic Programing: Framework para detección de intrusos usando DeLP | Semantic Scholar
- COVID-19 datascience work using machine learning covid-datascience/cc-covid-research.ipynb at master · luchux/covid-datascience · GitHub
- DNA Sequence alignment using constraint programming (UNL, Portugal) (PDF) Multiple sequence alignment correction using constraints | Luciano Guasco - Academia.edu
- Past Jobs: (https://www.linkedin.com/in/lguasco/)
- I am a computer scientist that worked for 10+ years as fullstack, with python and nodejs backends, with frontends Javascript - JQ - React - React Native - CSS3 and the fullstack ecosystem for development, testing and deployment.
- Worked in health care building a web / mobile app for doctor - patients ecosystem in San Francisco making the company grow 300x in a year.
- Worked with several startups and agencies building up apps in MeteorJS, NextJS, Android and IOS in several industries. Contributed to Meteor JS, Storybooks JS, and Next JS open source codebases.
- Co-founded FanFuel a startup in the sport/sponsorship ecosystem. CTO role building a mobile app to help athletes and brands to connect, with investment from Telstra, Australia.
- Worked with companies as data scientist lead, using machine learning and AI to solve complex problems as virtual assistants, data collection, pattern recognition and machine learning.