I find having mentors helps a lot in your Data Science learning journey. The reason is when you are structuring your thought process, you might need resources that have not come across before. This is where a mentor can come in.

The mentor can cut down your research time, guide your thought process and provide career advice. Thus we must select the right mentor, to ensure a smoother learning journey.

In this post, I am going to outline some steps in seeking the "right" mentor. Note that these are guidelines and feel free to take the appropriate steps necessary.

Who is a Good Mentor?

Personally, a good mentor will be one that can help you break the bottlenecks in your thought process, they can guide you without spoon feeding, and more importantly, they have your interest at heart.

To find a good mentor, here are some steps you can take. Patience is needed to seek a good mentor(s).

Step 1: Identify

The first step is to look for and identify one. Where to seek one? Check out your local tech community or special interest group. Attend their meetups. Try to be early or stay behind for a while and network with the community. Listen to the speakers and ask yourself if you are interested in working on similar projects to theirs.

Once you have a few names, check out their profile, Github or even blog site. Find out more about them, check if they have years of relevant experience working with data, how many projects have they worked on, do the projects pique your interest.

Till now if you have tick marks on their experience, the next step is to find out about their character and values, if possible. The reason is there can be people with very good experience but are terrible (condescending) people. (Most data scientists are nice, so there is no need to worry.)  Speak to people that they work with to find out more. Read their blog posts too.

Step 2: Seeking

Once you have identified a few of them, chat with them. It can be over a cup of coffee or during a networking opportunity (before or after a meetup). While chatting, it is for you to validate their experience, how technical they are and also their character and value. If the fit is there, ask for mentoring. Be specific, ask them what you are seeking, the kind of project you are interested in, what kind of mentoring you are looking at, and the amount of time needed from them.

Step 3: Be Proactive

You need to treat your mentor's time as a very precious resource. Be prepared. This is especially true if you are meeting after a workday. Prepare to show what was done so far in your project, state down the questions you are going to ask. If you can, ask your mentor if it is ok for you to send the questions in advance. If you can, do an additional round of research on your questions again, see if you can find answers for them.

At the end of the day, the mentor is volunteering their time (which they can spend with family and friends). So seek to make the maximum impact with the least amount of time spent. :)

Step 4: Show Appreciation & Gratitude

After a few mentoring sessions, please consider showing some gestures of appreciation. Remember, they are offering their expertise, experience and time with you. They have a choice not to. Tell them that you appreciate the opportunity to learn from them, it can be over a good meal,   help them with an errand, a gift of knowledge (books or vouchers), write a LinkedIn recommendation, do a shoutout, etc.


I want to emphasize again, that seeking good mentors, is very important to your Data Science career. Be patient and seek the right one. The right one can unlock tremendous benefits for you. Meanwhile, you can work on another important aspect and that is building up your project portfolio. :)

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