Be Resourceful — One Of The Most Important Skills To Succeed In Data Science
Yet this is one of the most forgotten skills
Being resourceful is the ability to find and use available resources to solve problems and achieve goals.
And there is not a more important trait to possess than resourcefulness in the pursuit of success in data science, and in life.
Having been in data science field for quite some time, I’ve always been studying and learning the attributes of many successful data scientists — be it professionally in their careers, or personally in their life.
And you may be thinking that to be a successful data scientist is nothing more than the combination in this Venn Diagram:
Technically speaking, there is nothing wrong with that and you’re absolutely correct. However, something is missing — YES, soft skills — and resourcefulness is one of the pieces to be successful as a data scientist after studying, understanding and talking with various data scientists.
In this post, you’ll see why being resourceful is extremely crucial to learn and pursue data science path and I’ll also share my experiences to hopefully show how you can use this forgotten skill in your pursuit of success in data science, and most importantly, in life.
So let’s get started!
1. Being Resourceful is a Mindset
Resourcefulness is a mindset. Period.
This is especially relevant when the goals — or the problems — you have set are difficult to achieve or you cannot envision a clear path to get to where you desire to go.
And this is perfectly fine. Many of us (including me) very often don’t have a clear path or approach to solve our problems to achieve our goals.
It’s okay to have uncertainties that lie ahead. But it’s not okay to stay stagnant, not going anywhere but to wait for some miracles to happen. Because chances are, they won’t happen. Sad to tell you the truth but reality is always harsh.
💡Resourcefulness is to be proactive
Particularly for aspiring data scientists to pursue a career path in data science, there are tons of resources out there waiting for being discovered. Yet, most of them tend to be a passive observer rather than being proactive to find and create their own resources.
When we talk about resources here, we mean books, online courses, open source projects (Kaggle etc.), hackathons and competitions, and most importantly, networks.
With a resourceful mindset we’re driven to find a way. There is no waiting. We’ll always try to find a way, always.
When I first started out to learn and pursue my career in data science, I was like other aspiring data scientists baffled by tons of resources out there, each of which claimed to be the best among all. Overwhelmed. I read as many book and articles as I could, asked for advice from as many data scientists as possible, took as many online courses (shitty and good) as I could, and made tons of mistakes as far as I could remember and learn from them.
The learning path was uncertain, but I was proactive. And ultimately, I filtered out some of the most useful resources that have helped me go into data science field at the shortest time possible. And I even wrote an article — How To Go Into Data Science? — to compile all the resources with practical guides. Hope you’ll find it helpful to you as well.
You see. When you are resourceful you don’t allow outside circumstances determine when or how you take action, or you’ll always settle for less.
An attitude of resourcefulness inspires out-of-the-box thinking, the generation of new ideas, and the ability to visualize all the possible ways to achieve what you desire.
Possessing a resourceful mindset requires you to stay positive. There is a solution to every problem, even if that means a change in direction.
2. Being Resourceful is a Skill
Resourcefulness is a skill.
And the good news is: this skill can be learned and mastered.
I’d not say I’ve mastered this skill as I am still a learner of being resourceful, now and will always be.
Solely having a resourceful mindset is not sufficient to solve problems and achieve our goals. And this is where the skills come in to bring the mindset into action.
Having skills in being resourceful is especially important in data science as this field is still young and there are no definite paths for it. It’s the subtlety that makes this field so much challenging, exciting and rewarding at the same time. And this is exactly why I am here writing about data science simply because I love it!
💡Resourcefulness is to know who/what to look for and what to ask
Let’s talk about who to look for to succeed in data science at work.
Admit it or not, we can’t master everything in data science and there must be something that we don’t know and understand. Therefore, finding the right people to seek help and ask for advice is extremely important.
You may be spending a few hours trying to make sense of some important technical concepts. But what if you approach and ask one of your friends or colleagues who is a Subject-Matter Expert (SME) in this domain? Chances are the past few hours could have been shortened into a few minutes or even lesser.
Sometimes the answer could be just one question away.
I got to be honest with you. During my first few months at work, I faced a lots of difficulties in terms of understanding domain knowledge, data pipeline being used, some technical jargons and many more. Yes I could have spent my time asking myself or frantically searching for answers online, but I decided to approach my team members and clarify my questions with them. Bang!! Most of the time the questions got answered and led me up to speed with the work.
But here is the tricky part.
Now that we know what and who to look for, we need to know what to ask and ask in the right and most efficient way. In other words, we need to know what and how to ask to right questions to solve our problems.
Besides seeking help from our colleagues, we google for help and answers as a data scientist. Stack Overflow, Data Science Central, Quora, Analytics Vidhya… You name it.
There were many times I typed in some keywords to search for explanation and solutions but Google returned me some resources that were not of my interest. Frustrated. I tried to tweak the keywords a bit and the results were entirely different that gave me more accurate results!
If there is one thing I learned from this experience: Not only is it important to ask the right questions, we have to search using the right keywords to get the best results.
Again, there are many resources out there. Be resourceful and learn from the suitable resources.
Final Thoughts
In short, resourcefulness is attained only when we combine the resourceful mindset and skills.
There has never been more noises than now in today’s digital era and thus, it is of utmost importance for us to extract signals in the vast ocean of information to make the most out of the resources.
Thank you for reading. I hope this article gave you a glimpse of the importance of being resourceful to achieve success in data science as well as in life.
As always, if you have any questions or comments feel free to leave your feedback below or you can always reach me on LinkedIn. Till then, see you in the next post! 😄
About the Author
Admond Lee is currently the Co-Founder/CTO of Staq — the #1 business banking API platform for Southeast Asia.
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