Data science has seen tremendous growth in the last couple of years because many industries deem it essential for growth.
However, with such a boom comes an influx of aspiring data scientists and students. And, if you find yourself among these students, you might be searching for ways to further develop your technical skills.
But do you really need a data science mentor, and if you do, where should you look? In this article, we will try to answer these and other questions you might have related to data science mentors.
So, first, let’s see what a data science mentor is.
A data science mentor is willing to give back to the data science community. They want to share their industry experience, technical expertise, and guidance to help aspiring data scientists build their careers.
If you’re unsure how a mentor could help you grow, let’s look at the top 3 benefits.
You have your books and classes; why would you need someone to mentor you in data science? Well, consider the following benefits:
Data science mentors can benefit data science students or beginners because they can provide helpful industry insights.
If you already have a good idea of what career path you want to take, a mentor can optimize your learning process by advising you on which tools or skills to master.
A data scientist mentor can suggest real-world data science projects you can work on to gain practical experience, which companies value more than education or course certificates.
That kind of hands-on knowledge will help you land your first job.
Many data science students leave with their master’s or PhD, believing they’ll easily land the best job. However, it’s never that easy, considering the number of data scientists is continually increasing.
A data science mentor can help you set realistic goals and give you the guidance and motivation needed to reach those goals. Mentors could also do mock interviews with you, which is something we value a lot at Interview Query, as it is a great way to prepare you for the real deal.
If you’re starting to see the value of a data science mentor, you might be wondering where you can actually find one.
The data science community is constantly expanding, but to find the best mentor, you should probably search in these three places:
LinkedIn is usually a business and employment-focused platform, but there are tons of communities/groups in which people help each other. This is especially true for data science communities.
For example, this data science group has over 80,000 members. This Power BI group for analysts has over 1,3 million members! With such large communities, there are bound to be a lot of people willing to provide mentorship.
Reddit is the go-to forum for finding all kinds of data science-related information. And with more than 1.7 million members, r/datascience is absolutely a place where you can find a data science mentor.
A good alternative might be r/dataanalysis.
While these community-based mentorships can be very useful for any data scientist looking to grow, finding the right mentor can be a hassle. But, if you want to skip that trial-and-error process of finding the right mentor, consider our coaching service at Interview Query.
Not only does it make finding the right mentor much easier, but you will also get a lot of value from these experts. With constructive and personalized feedback, guidance, real-world projects for practical experience, and other insider information, you will have access to all you need to ace your data science interview!
Now that you know where to look for data scientist mentors, let’s look at the steps to finding the right one.
Before you set out looking for a mentor, you will need to figure out your goals. Ask yourself: “What kind of growth am I looking for?”
Are you looking to improve specific technical skills or your management/communication skills to land a higher position, like a chief analytics officer?
Whatever your goals are, make them achievable.
Above, we mentioned three different sources for data science mentors—you should use all three. The more sources you use to find a mentor, the more likely you will find one that best fits your needs.
For LinkedIn, consider updating your profile and being more active in data science-related groups. Your ambition might lead to potential mentors.
For Reddit, either create your own post and ask for help or try to find posts already made by others, and open up a discussion in the comments. But specify exactly what kind of help you are looking for to filter out people unqualified to guide you in the right direction.
For Interview Query, check out the experts and their experience in data science and with coaching. Have a look at the pricing table as well to see what kind of plan best works for you.
If you managed to single out a couple of data science mentors from various sources, it’s time to see who can best help you with your goals.
Discuss how they would take on your shortcomings, how they could boost your practical knowledge, and the frequency of the coaching sessions.
After gathering this information, choose your mentor.
While a data science mentor should have tons of experience and a good understanding of necessary technical skills, in the end, you determine how much you’ll get out of the mentorship.
Fully commit to these mentoring sessions and be willing to learn. The more you engage with your mentor, the more you will get out of the whole experience.
Consider creating an overview of your progress to recognize how much you’ve developed over the course of the coaching.
Anyone just starting in the data science world and looking to build a career should consider connecting with a data science mentor. Following a mentor’s advice is the perfect way to elevate your skills and get ready for any future data science interviews.
Mentors might also be useful for people who’ve recently faced failures with data science projects. They need support to get them back on track.
While not necessary, data science mentors should have a curriculum plan or coaching program ready for their mentees, just like our experts do at Interview Query. With activities, objectives, and feedback during the coaching sessions, your mentor will be able to assess your progress.
A mentor can help with failures or setbacks in data science projects by giving you an objective root cause of your failures. With this analysis, you can figure out what went wrong and what to avoid doing next time.
It’s also important to remember that data science projects can be challenging, and you should never back away from one. A mentor can help you regain your confidence and motivation to tackle a new project.
Data science mentors were once beginners and faced failures, just like everyone else, but with the help of their community, they worked through their deficiencies. Today, they offer the same kind of help to you or anyone looking to grow as a data scientist.
With this guide, we hope you now understand why mentors can be beneficial and where and how to find the right one.
Finally, if you have trouble finding the best mentor, consider our coaching service, and we’ll vet the mentor for you.