Photo by Lucas Clarysse on Unsplash

How to Find a Data Scientist Job Part I

After several months of lay-off, I finally got a data scientist job in Sydney again. Here I’d like to share some tips about finding a data science job in Australia during this pandemic period.

Tips About interviewing

1. Stand during the virtual interview. Standing can make you more confident and give others a better impression. Standing can also make you feel more flexible and easy to use body language.
2. Make your self-introduction and research/work experience simple. I am a non-English background, English is one of my drawbacks, and virtual interview makes it even worse. I tried my best to make the self-introduction and experience part simple, emphasis on the main point, my contributions and results. I was asked to talk about my research during several interviews. I went through too many details, also covered too much math concept, afterwards, the feedback was that I have a solid theory background, but my communication skills need to be improved. So I practised with my wife many times, deleted the complex concepts, make more examples until she can understand my topic well. I would encourage you to practice interviewing with non-tech background people. One of the interview questions I have been asked was to explain the random forest algorithm to non-tech staff.
3. Use whiteboard if you have to explain some complex concept. Both Zoom and google meeting provide whiteboard tool for you during virtual video calls. Draw a picture showing your thought could be extremely helpful.
4. Do meditation before interviews. Meditation helps me to calm down.
5. Ask for feedback after the interview. Feedback is extremely helpful. You can get to know where to improve yourself most efficiently.
6. Get very familiar with the basic concepts about machine learning, such as PCA, linear regression etc. I wasted several opportunities because of lacking essential ML knowledge.
7. Research about the company before the interview. View their webpage, read the company culture/principles, prepare some stories which align with their culture. Some of the interview questions may be related to the business of the company.
8. Record yourself doing mock interviews.

It will be painful to watch, but infinitely useful. Remember that every mistake you make is an opportunity to grow. Every weakness you spot is an area you can improve. Every “um”, “ah”, “uh”, and “like” is an opportunity to become a better speaker. Record yourself, watch yourself, be critical, and learn from the experience. This is how you get better at interviewing.

Tips about job searching:

1. Do some ML projects/Kaggle competitions. For a data scientist role in Australian, employers pay more attention to your project/working experience. There are quite a few companies that care about your coding skills. I spent plenty of time to practise solving problems on leetcode. I found one out of ten companies have interests in problem-solving skills.
2. Do the take-home exercise/online assessment as early as you can. Some of the tasks may not have a deadline, however, there may be some other candidates doing the exercise at the same time, if they submitted the exercise one week earlier than you, they may get the offer before you submit your solution.
3. Get to know more people, have more connections on LinkedIn. I heard that two out of three people got their job via referring. I got my first data scientist job by referring. Besides, many companies in Australia rely on agents to hire talented people.
4. Make good use of job search websites. Frequently search keywords such as “Machine Learning” using Seek, Indeed, LinkedIn. Subscribe the job alert service from automatic job searching websites such as nuevoo, Adzuna, they will send you new related job opportunities daily.
5. Apply for as many jobs as you can. You have nothing to lose, applying for a job costs only several seconds. Some of the Data Scientist jobs require years of experience, but you can still try to apply for them. I even got interview opportunities for senior NLP engineer and senior data engineer roles although I do not have any experience in these areas. I also applied for some senior Data Scientist roles posted by agents, although I was not successful, the agents still contacted me and offered other roles match my experience better.
6. Permanent resident is important, but there are still some companies that do not require it. I got my first data scientist job without PR. Besides, if you have the ability to find a data scientist job, you may eligible for applying for the 858 global talent visa.
7. If you failed for an interview, you can check the company’s linkedin page couple of months later, to see if there is somebody joined the company with the same position, so you can compare your own profile with his/hers, then you will know where to improve.

Learning Resources:

0. Approaching almost any machine learning problem. This book not only gives an intuitive explanation of ML concepts, but also the code of the implementation. After reading the book, you can even have a taste of good coding practice.

1. Machine Learning Course on Coursera and CS229 Machine Learning course at Standford University.

2. How to win a Data Science Competition: Learn from Top Kagglers, a useful course about data science theory as well as practice.

3. Neural Networks and Deep Learning book provides a great intuition about deep learning.

4. Deep Learning book

5. Pattern Recognization and Machine Learning book, if you want to conduct in-depth research about machine learning.

Comment if you have any question. I have written another story to share some frequently asked data scientist interviewing questions. And several more tips summarized after recruiting team members.

Last but not least, if you are refused many times, it’s quite normal, cheer up, calm down and keep going, trust yourself and improve yourself, you will find a great job anyway.