Full stack Developer- Taiwan

Who You Are

You enjoy working on different projects and aren't afraid to call your baby ugly. You know the power of fast iteration, and fully embrace the test & learn methodology. You're an independent thinker, but also collaborative and always willing to lend a hand.

You're able to be autonomous, yet understand the importance of communication and alignment. Loosely coupled, tightly aligned, as they say. You are not married to any technology or solution and believe in the right tool for the job.

You not only believe in being data-driven, but you live it. This means you understand that you can't improve what you don't measure.

Responsibilities:

• conceptualize, ideate, and iterate on problems, solutions, and ideas in order to build out a product roadmap of ideas to build
• design, implement, and deploy solutions to problems and prototypes of ideas which includes the full life cycle of software development in an agile development environment
• learn whatever you need to learn as we explore new ideas and projects, so that we can build the next big thing
• measure product performance by investing in and building the necessary monitoring and analytics tools

Requirements

• Excellent written and verbal communication skills in English.

(for full stack)

• at least 4 years of full-stack software engineering experience as part of a team of other software engineers
• experience with front-end development frameworks such as React, Vue.js, or Next.js and CSS libraries like tailwindcss or Bootstrap
• experience with backend development including API design and development, database design and data modeling, performance tuning, service-oriented architecture (SOA) or microservices
• experience with MVC frameworks like Django or Ruby on Rails (RoR)
• experience with the Python programming language
• experience with cloud platforms like Google Cloud Platform (GCP) or Amazon Web Services (AWS)

(for data science)

• experience with data science notebooks like Jupyter, Zeppelin, or Google Colab
• experience with data science libraries like pandas, scikit-learn, or TensorFlow
• experience with data pipelines, ELT / ETL processes, and data wrangling
• general understanding of machine learning concepts like supervised vs. unsupervised learning, training sets, and overfitting

Location: A hybrid work model: a mixture of in-office (below) and remote work