lieuzh
Group testing: how do you test 1k people with less than 100 tests?
Type I and Type II Progress
Pair work: the One Weird Trick to finally ship your side projects
Ask HN: Books Like “Without the Hot Air” but in a different domain?
Read MacKay's book—excellent, albeit somewhat dated. I really like the "accounting" approach of doing up the numbers, and wonder if there are books similar to it on topics like carbon emissions, UBI (whether it's feasible, do the sums add up), and so on.
- 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.