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Here’s What Lead Data Scientist Have To Say about Becoming Indespensible

The Mindset of an Elite Data Scientist

Photo by Aron Visuals on Unsplash
Photo by Aron Visuals on Unsplash

I intend on speaking with many more lead data scientists, however, if I am totally honest, the reasoning behind why I reached out to them was never to make a blog post.

In fact, the reason I decided to reach out to some of the leaders in our field is that I wanted to gain a better understanding of their mindset. The mindset of a Lead Data Scientist! Quite frankly, I’ve never experienced speaking to one prior to this initiative, let alone working under one – I’ve only ever been the sole Data Scientist (or Machine Learning Engineer).

After speaking to the first two, I left feeling extremely inspired and thinking how life-changing the information and advice I was receiving first hand was. In a blink, I recalled the mission of my blog… To fuel the growth of indispensable Data Scientists, which then resulted in this write up. To further add, my initial instinct was also reiterated to me by one of the Lead Data Scientist, Thom Ives namely, who commissioned me to pass on the message to the community – A modern-day Andrew Carnegie and Napoleon Hill sort of thing, just quite far off being exactly that.

With my goal and mission now aligned, I set out to speak to whoever I could find in my LinkedIn connections with "Lead" or "Senior" Data Scientist in their tagline. I Formalised my approach and added a sprinkle of flattery, just to tickle the ego (deliberately), and sent a message to them all.

Hi [Insert Name],

I am conducting a mini study where I hope to gain insight into The mindset of an Elite Data Scientist hence why I have reached out to you.

I was wondering if it’s possible I steal 30 minutes of your time within the next week (or so) to ask you some questions in a private discussion (either via Zoom, Google Meet, Teams, or whatever is most suitable for you) in order to gain more insight into the mindset behind what gets the leaders of Data science to tick 😊

Regards,

Kurtis

To my surprise most said yes, of course after playing down the elite status I had given them. In other words, the flattery tactic worked because it got them responding – which is perfect as it would open the door to many conversations in the future.


Junior Data Scientist vs Lead Data Scientist

A Junior Data Scientist is expected to have a good fundamental knowledge of Data Science, which in turn allows them to be moderately independent although they may seek assistance from senior colleagues occasionally. In general, someone who is seen as Junior does not have much hands-on professional experience for one reason or another.

Contrastingly, A Lead Data Scientist is expected to have a firm understanding of the main concepts and techniques in Data Science (this includes knowing the pros and cons of them as well). They are expected to of worked on many projects, hence developing their hands-on professional experience technically and domain knowledge (the level of domain knowledge required may vary from company to company).

The unspoken difference between Junior and Senior Data Scientist by Mısra Turp details the fundamental requirements and tasks taken on by each role greatly – highly recommended read!

Why Does It Matter?

Why does it matter? Great question! In my opinion, I believe it’s important to understand the standard path to reach a particular destination, for instance, if we set out on a journey to Hyde Park. Having a clear idea of how to get to the park would be essential for us to reach our destination in the first place but in the event that we are faced with an obstacle like the central line is not running for some reason, since we have a clear destination, navigating around the obstacle is a much more seamless process because we know where we’d like to end up.

The same is true for our careers. Having a clear idea of the path to take makes decision making about our future much more seamless, as the decision we make would be in accordance with where it is we are aiming to go. The more informed we are about where we are going, the easier decisions about how to get there would become – And to readers of my blog, I assume you have decided to become an indispensable Data Scientist.

Alternatively, we can decide to not gain a clear idea of what is necessary to get to where we want to go. In this situation, a lot of decisions are based upon how we feel at a particular time, hence we end up doing more things like ** competing** in 200 Kaggle competitions, or taking 700 programming tests.

As you can see, these things may not necessarily be bad, but they most definitely can be delays because we have become so consumed with doing more things in hopes of someday arriving at where we would like to be.

"When I’m chasing my goals, busy doing everything I think I must do to achieve them, I can sometimes become more of a Human Doing as opposed to a Human Being." – Tim Hayes

Note: I know being an indispensable Data Scientist does not equate to being a Lead Data Scientist – I.e. one may decide to start an company and use their Data Science skill to help drive the company to greatness

The Missing Ingredient

Given the expectations presented in the "Junior Data Scientist vs Lead Data Scientist" section, one would think that immense technical ability is the sheer distinction between someone that is a Lead Data Scientist and someone that is Junior.

To some degree, I agree. Although I believe it’s possible for someone Junior to have more equal, or maybe even more technical ability than someone senior, this could be due to my athletic background where it is not unusual for a junior football player to be more gifted than a senior player – Look at Kylian Mbappe for example.

Then I thought maybe it is the experience that one has acquired over time. Although also correct to some degree, I quickly dismissed the thought as I’d be assuming that longevity in the field plays a significant role in determining whether one is "qualified" for the Lead Data Scientist role. This would mean I’d have to wait some 10–20 years before I can get a look in, and yes it may be worth the wait, but…

The thought left me in a confused state; "How do I go from where I am now (I consider myself to be a Junior Data Scientist) to where I want to be?"

As I’ve mentioned time and time again. The goal is indispensability, and though indispensability and Lead Data Scientist are not synonymous (in my opinion), it is a very good reference point to start from.

So what did the Lead Data Scientists I spoke to determine as the missing ingredient to becoming an indispensable Data Scientist?– I’ve spoken to 4 as of writing this and have many more in the pipeline. They all said the same thing in many different ways, however one summarised it beautifully into one word…

"CARE!"

You have to care about the companies objectives, you have to care about clients needs, you have to care about your colleagues, you have to care about the impact of your work. YOU HAVE TO CARE!

Many of the material and/or status goals we wish for, such as becoming an indispensable Data Scientist, are the product of value we add to others, meaning we will reap them as a result of our service, therefore too much emphasis on the product may lead to frustration.

This is not to say that skills and experience do not play a highly important role in the ascent towards indispensability. If you have great technical skills you can work on more complex tasks. Similarly, with bags of experience, you could probably sniff out a problem before we even get there. Nonetheless, if you have no care in the world other than your own personal needs, you’ll probably be considered as the jerk that nobody wants to work with, thereby hindering your progress.

Generally, what may happen in this scenario is someone with half the skill and/or experience but is a passionate carer comes along, and with some training, you become more and more dispensable.

The Capacity to Care

It’s rare to hear care being spoken of as a skill yet alone what will advance your Data Science career but when I thought of the concept, it made more and more sense – For instance, what we care about would determine the skills we decide to learn.

If it is still not so clear, here are 3 ways we can begin to care without having a Lead Data Scientist title:

  • Care for What others are going through when you address them – this entails getting to know the people on some level (which I was initially taught is taboo in the work environment, but I now beg to differ)
  • Be observant of the needs of others and seek to fulfill them with your current skills or develop your skills so you are capable of solving them in the future.
  • Check-in with people – Whether it’s other people on your team or a client, regular communication to get and/or give updates shows you are interested in the work you are doing. You Care!

In other words, be a Data Scientist that acts more than they talk. Even if you don’t have the skills in the present moment, there is something you can do to care about someone else!

"We Data Scientist hold the torch for the future in our hands so we must serve with our skills rather than wait to be served" – Kurtis Pykes

Scott T. Clendaniel recommended me a book to read, which I have read before, though when I re-read it with this new paradigm in mind, I instantly saw the fuller picture of what all the people I have been speaking to were saying to me – The book is called "The 7 Habits of Highly Effective People" or what I now refer to as "The Corporate Bible".

Wrap Up

The new paradigm I’ve received has come as a shock to me and may come as a shock to you. Yes, it is important to develop your technical ability, yes it is important to get as much experience as you can. In the same way, it is important you develop your ability to care for the people that are working with you, as well as those you impact.

Thank you very much for reading this post to the end, Let’s continue the conversation on LinkedIn…

Kurtis Pykes – AI Writer – Towards Data Science | LinkedIn


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