Building a Data Science Brand
With DATAcated®’s Kate Strachnyi
What does it mean to develop a brand in data science? “Picture a group of people who know you well,” says Kate Strachnyi, founder of DATAcated®. “What do they say about you when you’re not there? That’s your brand.” Kate tells us that even if you are not putting yourself out there aggressively on social media, you’re going to have a brand whether you would like to or not. Your brand is your reputation, and if you want to succeed in a data science career it is important to make sure you have a good one.
“I personally have received so many benefits of having a data science brand,” Kate says. “It’s basically a way that people can start to funnel good things your way whether that’s opportunities or jobs or speaking gigs. If they know that you’re the person who’s good at X—in this case data—you’re who comes to mind first when they hear that term.”
Data science continues to grow as one of the hottest career fields in the country, ranking as the “number one job in America” in four of the past five years, according to Glassdoor. Finding a way to make yourself stand out as a leading voice in the industry can be key to demanding the best positions and the highest salaries. It can also let you make your mark on the data science industry as a whole and make some pretty cool connections along the way. Connections just like… Kate Strachnyi! Let’s dig a little more into her data science journey.
Dedicated to Data
Kate herself has come a long way to become the person that comes to mind for so many in the industry when it comes to data science branding. Born in Tajikistan, Kate did not attend school for the first time until her family moved to America when she was 9 years old. Learning basics like math and English for the first time as a fourth grader did not slow her down, however. Fast-forward a little over a decade and Kate has graduated from college early and was on her way to a career in finance.
Kate spent much of her twenties in the financial sector before approaching motherhood caused her to rethink her priorities and she approached her company to make a change. “I basically told them ‘I don’t want to work nights and weekends, I don’t want to travel, I want to see my kids,’” Kate told us. They were able to work with her and devise a role that allowed her to start working from home, and Kate confesses that, at that point, she was not even particularly concerned what the role was. “But I was lucky enough that it was a data analytics role and that was my first entry point into the world of data. It was love at first sight.”
Data was a new field for Kate, and she was invested in succeeding in the role. “So, what I started doing was posting online whenever I learned a new concept, researching best practices and sharing that with the data community,” Kate explains. “That was really the early stages of how this DATAcated® thing came to be. At first it wasn’t intentional, I was not setting out to be building a brand in the data community but what happened over time was the more I engaged in the community, the more content I put out there, the more it snowballed into this bigger following, this bigger thing that eventually became known as DATAcated®.” Kate opened up the DATAcated Academy, a DATAcated® media company where she partners with organizations to amplify their messages on social media, and the DATAcated Conference, which Kate says is taking much of her time these days.
So, how did she make it all happen? And what can you do to do the same? Discover Data Science sat down with Kate to gain her unique insights on establishing a data science brand presence.
Be Intentional About Your Data Science Brand
“I’d say the most important step is knowing what your brand is or what you want it to be,” Kate says. “Start by assessing what you want to be known as or known for, and that might be difficult for some people. A quick easy way to do this is to ask your colleagues what you’re good at and what comes to mind when you think of me. If that’s not in line with what you want to be known as then you’re probably not doing a good job of building that brand.”
A lot of these decision come down to what Kate calls being intentional. “If the first step is defining your brand, making sure that it represents how you want to be known, then number two is to create content that is in line with your brand,” Kate says. “As an example, you might be motivated to show a funny video of your dog playing in the snow. You might get a lot of likes and a lot of engagements but ask yourself, ‘Is this really the attention that I’m looking for? Is this in line with the brand I’m creating?’ Maybe it is! But be intentional with it, and make sure it’s aligned with what you defined in the first place.”
Kate urges you to try to keep your posting roughly 90% professional, especially when it comes to branding and data science, but says this does not mean you should worry too much about showing a little bit of your personal side as well. “For example, I talk about my running online because I think people can connect to that or relate to that, or I talk about my kids, there’s a balance,” Kate says. “You’ll occasionally see someone who go the other way around and you’ll see more personal. That can work as well, it depends on the brand you are building, but for the data world I’d recommend keeping it 90% professional.”
Kate knows a lot of people start off may feel overwhelmed by the number of voices that are already contributing a lot to the data science conversation. One of the top 5 tips of LinkedIn experts to build your data science brand (one of whom is Kate herself) is actually to lean-in to that sense of imposter syndrome. “People don’t know always what they have to say that’s different,” Kate says. “I think that goes to sharing your unique perspective. Let’s say you are starting out in this space, or you are transitioning from a different industry or specialization, and you want to get into data science. There are other people like you who want to hear that unique perspective. Wherever you are right now, share that journey with the community, so they can actually feel like they’re going along this journey with you.”
Start Small and Work Your Way Up
For those who are not sure exactly where to start, a point Kate stresses is that you do not need to start by posting your own content at all in order to build your brand. “I have friends who don’t put out their own original content, but they engage with the community, commenting on people’s content and engaging with other commenters.” This, Kate explains, is also a form of building your brand. “You can be a supporter; you can take the time to engage with those you agree and disagree with and put your perspectives out that way. Your name will still get recognized.”
Kate believes this is the easiest approach since you’re not putting yourself out there right away. Eventually, though, posting your content will be the next step. “I know that can be scary, it was scary for me at first as well. Then, I think the ramping up is start posting a couple times a week, to get a sense of how that works for you. It will allow you to help getting over that fear that somebody you know will see your content. I think that is a fear people have, which may seem weird, because you’d think people would be more worried of the reaction of strangers, but no. People tend to be more worried about if my colleague or sibling or friend sees my content, what are they going to think?”
For Kate, she began posting just once every one or two weeks. “I’d say ‘I’m learning this cool new thing in Tableau or data visualization,’ and two or three people would comment or like it. It was that ‘Aha!’ moment of ‘Oh, wow, people care about this, and there’s a community out there who want to support me and see me succeed.’” So, Kate continued posting based on that engagement and she jokes that the addiction of social media left her wanting more. “A couple of us in the data community, especially on LinkedIn, had started become friends. We started hosting data science office hours, where every week or every couple of weeks we would do a live session on YouTube on a specific topic, like data storytelling. The crowd that turned out was probably 20-30 people at first, it wasn’t huge, but it was enough of an audience to keep us coming back and it started helping build that community.”
The pivotal moment where Kate realized she had really started achieving something came a year later, when LinkedIn selected her as one of 2018’s top voices of data science and analytics. “I thought ‘Oh wow, this is a thing now,’” Kate says. “I couldn’t believe it, and that’s when I started taking this more seriously and started being more thoughtful about the kind of content that I was putting out there. I was selected the next year too, and that’s got to be the moment where I realized this is real.”
Authenticity
Kate talks about building a data science brand presence in terms of showcasing the ‘you’ that you want to be perceived as, but she thinks it is critically important that you do not go as far as to present yourself inauthentically. She acknowledges this can seem like a fine line, but it is an important one not to cross. As data scientist Admond Lee defines it, “Personal branding is about being YOU — the authentic self with your belief, your own story and experience that demonstrates expertise and authority in your niche.”
“Being yourself is truly the easiest way to put yourself out there on social media,” Kate tells us. “You might pull inspiration from others, but whoever they are, there’s no need for two of them in this space. Show people who you are, don’t be afraid to put yourself out there.” She mentions one of her favorite quotes as a child, from Happy Birthday to You! by Dr. Seuss: “Today you are you, that is truer than true. There is no one alive who is youer than you.”
To this end, Kate also surges people starting out not try to automate this process. “There are automation tools available that can search the web and post on your behalf, so you don’t have to touch anything,” Kate says, but from her experience those people get almost no engagement. “It’s very clear when these things are automated and programmed. Be authentic and show up as humanly as possible in this automated world.”
Consistency
An avid runner herself, Kate compared building a brand in data science to physical fitness in terms of consistency. After all, if you are trying to get in shape then doing 100 pushups one day and then nothing for a month is not going to get you there. “It’s what allowed me to build this DATAcated® brand,” she says. “Showing up every day with content. For me, I’m sure to show up five times a day.”
Kate realizes that not everyone is going to be able to do so much at first, but she urges you to keep your data science posts consistent either way. “That doesn’t mean you always have to produce the same types of content, feel free to diversify—put out some videos and blog posts, appear on the podcasts of others in the industry. But the messaging should always be on brand.”
She recommends posting at least four or five times a week once you begin really ramping up and trying to be a bit more aggressive on building your brand. “In terms of timing, I don’t think you need to be really structured with it,” Kate says. “I know a lot of social media consultants might always advise you to post at 10 am Eastern because that’s when their data suggests engagement’s hot or will tell you to post with these exact hashtags, but I say mix it up. Post at midnight, post on weekends. It doesn’t really matter. Yes, there may be more engagement at 10 am Eastern on a Tuesday, but chances are everyone has read the same articles by the same social media consultants and are all posting at the same time on the same day. So, if you post on your own schedule than you have a lot less competition for the same eyeballs you’re trying to get to recognize your brand.”
Conclusion
The U.S. Bureau of Labor Statistics projects a 27.9% growth in data science occupations through 2026. LinkedIn reported in 2018 that there was a shortage of over 151,000 data scientists across the United States in 2018, particularly in major metro areas like New York City, San Francisco, and Los Angeles. Clearly, data science remains a career path on the rise. If this a field that you are interested in, and if you can establish yourself as leading voice in the data science world through your brand presence, you will have your pick of top companies and top positions in the profession.
For more from Kate, be sure to read her recent interview with the AI Time Journal and check out her DATAcated Conference!
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