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There are two common groups of people that approach me on the question, "How can I break into data science?" The two groups are fresh graduates and mid-career changers.

For fresh graduates, especially those that has "Data Science" or "Artificial Intelligence" in their degrees, they can usually get past the HR filter. What is likely to stop them from getting the job interview will be the practical experience. The solution to getting the job, after passing the HR filter, is to build inpidual project portfolio, preferably passion instead of academic ones.

For mid-career changers, there are advantages that you have and should accentuate them in your resume.

In this article, I will share with you what they are and, in my opinion, what you can do to increase your chance.

Domain Expertise

After working for a while now, your domain expertise will be something that is of value to your potential employer. In fact, what I recommend is that you become a data champion in your current company.

Since you are familiar with the domain, you will understand how the data is collected, what is good quality data, etc. And you are in the right place to use these data to assist your current company to tap into data science.

Take advantage of it!

If you decide to move to another job, try to stay with the domain that you are familiar with. You might be in a certain industry but business functions will be what you should focus on, to accentuate that advantage. For instance, if you are in the finance department of the logistics industry, you might want to focus your job search on the finance function instead.


​Now at this point, you might have the question, "How do I make the switch then? Yes, I noted that you want me to get a portfolio but I cannot find a dataset to work with."

What I suggest then is that you should at least show your proficiency in the tools, especially visualization tools as that is where the quick-wins are.

In addition to the proficiency in tools, you might want to put down some thoughts, perhaps what are the possible projects that you will like to do if given a chance. This can help your future employer to gauge:

  • Firstly, how fast hiring you can "bear fruit"
  • Secondly, how much you understand the domain and your thought process in putting data to use for the particular domain.

Team Player

Another advantage that mid-career changers should have and that is working in teams. Data Science is a team sport. You will have to work with different groups of stakeholders and performing well in a team environment is very important.

Give your working experience, you should have plenty of experience in working in teams. Show that in your resume, let your potential employer know that you can be a team player and if needed, lead a project.

State all the projects, the roles that you have played in each one of them, and also the results/impact from these projects. This can help your potential employer quantify or at least infer how you are as a team player.

Communication Skills

Over the years of working, as a mid-career changer, you will have accumulated a lot of experience in communicating with different groups of people. Communication is a very important skill for a data scientist/analyst because we need to communicate with many groups of people during our work. We have to communicate with machine learning engineers, data engineers, business users, top management, etc and each group speaks different languages. One group does IT technical speak, another group talks in dollars and cents, another group talks in pipelines and tasks scheduling, etc.

Being able to communicate well will be an advantage that mid-career changers will have gained through working experience. Again, try to put as many examples of it inside your resume, show that you are a skilled communicator. Try to portray that during your interview as well.


Written by

Koo Ping Shung

President and Co-Founder, AI Professionals Association

Co-Founder and Practicum Director, Data Science Rex Pte. Ltd.

Industry Innovation Mentor, AI Singapore

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