I'm a Politics, Philosophy and Economics (PPE) student at Oxford who has been programming for 5 years. Despite my degree, I've self-taught myself computer science: I've taken MOOCs on algorithms and data structures, computer architecture, databases, parallel programming, and machine learning, amongst others. I've done several internships as a software engineer and data scientist. The most exciting project I'm working on now is writing Apache Spark programs for a Raspberry Pi cluster to do analysis on >6 billion data points.
I am looking for a full-time job in 2020 after graduation. I have wanted to be a SWE for the longest time, but recently I realised that my comparative advantage lies more in data science: my degree has given me training in economics, statistics, experiment design, and data analysis and visualisation (Python, R).
I am still happy to take up a generalist SWE role, although I probably won't be as quick in the interview as CS grads who have plenty of experience grinding Leetcode. What I'm really interested in is a role where my knowledge of economics and statistics (and ability to write well!) can bring value to a company over and above a CS grad.
- Remote: Yes
- Willing to relocate: Yes
- Technologies: Python, JavaScript, Scala, Spark, R, Node.js, Tensorflow, PostgreSQL, Linux, Git
- Resume: https://lieuzhenghong.com/resume/resume_25_aug_2019.pdf
- Email: lieuzhenghong[at]gmail.com
I'm a Politics, Philosophy and Economics (PPE) student at Oxford who has been programming for 5 years. Despite my degree, I've self-taught myself computer science: I've taken MOOCs on algorithms and data structures, computer architecture, databases, parallel programming, and machine learning, amongst others. I've done several internships as a software engineer and data scientist. The most exciting project I'm working on now is writing Apache Spark programs for a Raspberry Pi cluster to do analysis on >6 billion data points.
I am looking for a full-time job in 2020 after graduation. I have wanted to be a SWE for the longest time, but recently I realised that my comparative advantage lies more in data science: my degree has given me training in economics, statistics, experiment design, and data analysis and visualisation (Python, R).
I am still happy to take up a generalist SWE role, although I probably won't be as quick in the interview as CS grads who have plenty of experience grinding Leetcode. What I'm really interested in is a role where my knowledge of economics and statistics (and ability to write well!) can bring value to a company over and above a CS grad.