Original article was published by Kurtis Pykes on Artificial Intelligence on Medium
Why the Big Fuss?
Now we have the definitions out of the way, the next step is to explain why branding is important in Data Science and for this section, I have 2 key reasons why building a personal brand as a Data Scientist is important in my opinion;
Aid in The Vetting Process
Ever since I embarked on my job hunt journey, there is one thing I am noticing more than anything…
The term “Data Science” is extremely broad.
What is regarded as Data Science by one company may be regarded as a Data Analyst by another, Machine Learning Engineer by the next, a Quant, or a Jack of all trades; Wherever you go, the definition of the role of a “Data Scientist” may change… Sometimes, drastically!
In part, I am now beginning to feel some empathy towards hiring managers, HR Departments, etc, because they are likely receiving tons of beautiful applications every single day which are totally unrelated to what it is they specifically want. Furthermore, let’s not talk about the burden of the person who has to write the job description.
It may be easy to write the job description of an analyst, but the lines become extremely blurred when you begin to define the qualities that you’d want in a Data Scientist. To some extent, this confusion has even made writing the descriptions of other roles, such as an analyst, more difficult — I have seen analyst roles that require modelling skills, which may of sparked a virtual riot if the Data Science God’s (just a fictional character, please don’t google it) got a grip of it.
I highly recommend you read “Data Science has become too Vague” by Thomas Nield — It discusses the evolution of Data Science, and why Thomas believes we should dissolve the term “Data Science” and be more specialized. I think he made some really good points.
“Harvard created a void called “data science” and everyone raced to fill it. SQL developers, analysts, researchers, quants, statisticians, physicists, biologists, and a myriad of other professionals rebranded themselves as “data science” professionals.” — An extract from Data Science has become too Vague, Thomas Nield
Given the Identity crisis we are facing in the Data Science field, personal branding comes in to alleviate one from the crowd into the “exactly what we were looking for” category.
For instance, if you are apart of the Data Science community on LinkedIn, you’ve probably heard of Kate Strachnyi. You are never going to look at Kate’s profile and think ‘Hmmm… She is exactly who we’ve been looking for to solve our credit card fraud detection problem’ because all she ever talks about is Data Visualisation.
Now, that is not to say that Kate can’t do modelling (of which I truly do not know), but I sure well know she can build a wicked Dashboard! And a company that is looking for someone to build intricate dashboards will instantly see Kate’s personal branding and know exactly what she is about.
In the same way, I don’t believe Microsoft will call Andrew Ng to come and build an interactive Dashboard for them because going off his Coursera courses, of which are some of the best courses on Machine Learning and Deep Learning, he’s probably bloody well good at problem formulation and modelling (as well as other things).
Essentially, your Personal Branding will clear up the fog around the definition of a Data Scientist because you have already defined where your strengths lay.
Unlimited Upside and Little downside
I must say, it is an ego tickle when a PhD Student sends you a direct message telling you of how much your work has inspired them. However, beyond the lovely messages (and the occasional hate mail), the opportunities are endless.
“Where there is unlimited upside and very little downside, take the risk!”
No doubt in the beginning things will be slow. It may take 7, 8, 9 or 10 months to gain traction, but somewhere down the line (even sooner for some really exceptional people), your inbox will be flooded with opportunities and connection request — I am talking from experience.
To put things into perspective, I recently was a guest on a podcast (hopefully it would be released in earlier Janurary) and if you told me this would happen at the start of the year, I’d of scoffed at you whilst I failed to interpret the results of a Decision Tree.
Branding yourself will put you in uncomfortable positions that will force you to grow quicker than if you shy’d away.
Aside from the opportunities, recall above we stated ‘a brand remains unique’, and that is because you defined the vision and your values.
If you think of some of the most successful companies in the world today such as Apple and Nike, who have both reaped the benefits of having a strong brand. They rarely delve into the logistics of a product and what it does. Heck, I can’t tell the difference between the last 6 iPhones but I still got one and many others are still buying their products.
Your brand, which describes where you are going (your vision) and what you value, is what will attract people to you!
Admond Lee wrote a great piece that details the upside of creating a personal brand and discusses more in-depth about the success of companies due to their brand— Why You Should Build Your Personal Brand as A Data Scientist.
If I’ve sold you…
Yoel Zeldes wrote a good blog that serves as a good starting point for building a personal brand — How to Build Your Personal Brand as a Data Scientist