How to Make Friends and NOT Alienate people (on LinkedIn)

Inna Saboshchuk
DATAcated
6 min readApr 25, 2021

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In my pre-pandemic life in-person events (like conferences, meet and greets, and talks by people I wanted to learn from) were key to developing a network of like-minded professionals who would help me learn and thrive in my career. In my particular case, I was in a foreign country where I didn’t know anyone, and I was pushing to make a jump from academia to private sector data science. It was imperative for me to interact with people already in the field to decipher how to go about entering the data science world, succeeding in my work, learning about the work of others to become inspired, and possibly MOST importantly to make friends!

One of the many unfortunate side effects of this pandemic is that these events are no longer possible. Though I must say, I quickly learned that LinkedIn is an excellent (and possibly even more efficient) substitute to these in person get togethers. Based on my LinkedIn inbox, I see that others have come to the same conclusion and are using the platform to build their networks. Also based on my Inbox, I would like to give you some tips on how to go about building this network and not alienating people who might otherwise be very willing to help you. If you’ve been actively trying to reach out to people on LinkedIn with little success, I hope these tips are helpful to you.

Stop focusing on getting a job, and start focusing on making friends

I understand and have extraordinary empathy for the fact that the economy is not at its best, the job market is tough, and this could often lead to desperation in what you’re willing to do to get hired.

My empathy aside, if you are a stranger on the internet, I am never going to simply recommend you for a job. How can I possibly know if you are a good potential data scientist if I’ve never even spoken to you? If you want me to recommend you, then you really need to give me the chance to get to know you.

If you’ve ever heard me speak or read any of my articles you’ve probably already heard me say my favorite catch phrase “You can’t fake it.” I am not trying to encourage you to pretend that you want to get to know me. I am encouraging you to change the way you think. You want to be a data scientist? That is a field that has already made 12 developments by the time you finish reading this sentence. Staying up to date is key, and one of the BEST ways to do so is by having friends who are passionate about data science and want to talk about it with you. Once you have given a successful data professional the opportunity to get to know you and how you think, the chances of having your CV passed on increases exponentially.

Even if your ultimate goal IS to get a job, this network you are creating is something that will serve you long after you’ve already achieved your goal. So seriously, make friends, don’t just send CVs.

Post content, and engage with the content of others

Now you are probably thinking “Great Inna, I would love to make friends, but how do I even get these influencers to pay attention to me?”

First, you’re going to have to risk a little. In my conversations with people, I see that many are very nervous about posting their thoughts online because they’re embarrassed about potentially saying the wrong thing, or not getting enough likes or being judged by strangers. If you want to get noticed, you’re going to have to be a little brave.

Are you working on any interesting side project? Post the details on LinkedIn! Add hashtags so that more people see what you’ve done. If you’ve already had some pleasant interactions with people on LinkedIn, tag them and explicitly and ask them for feedback (I really wouldn’t tag people you’ve never spoken to before, this could also just cause the person to be frustrated that you are asking something of them when they don’t even know you). This already helps me see what you’re working on, and that you are in fact passionate about this field, which is one of the traits employers care about most.

Do you have a unique thought about something data science related? Again, post it. Add hashtags, tag people, help others see the way you think!

Do you have an interesting thought about something an influencer has posted? If you read an article or post written by an influencer, your comments will have a substantial audience because the influencer has a substantial audience. Even if the person making the post does not directly respond to you OTHER people in the field will see what you wrote and potentially respond. As a side note “great article!” is not really the kind of post I’m talking about. Again, the goal is to show others how you think and add value to the conversation. A better comment is one that considers the content of the post and responds directly to it. For example, I recently made a post with an example of a bad data visualization, and a lot of people responded with suggestions for how they would have presented the data in a more digestible way. From this post, a lot of people caught my eye and after a few exchanges I now consider them part of my network and look forward to what they have to say in their own posts.

You are playing the long game

Unfortunately, 1 week of posting and engaging is not going to do the trick. It takes time to get traction and gain attention from people who you want to interact with. The first post I ever made had about 50 views and 3 likes from my friends. This is incredibly discouraging and makes you want to give up, BUT DON’T. Persevere, and continue to post, engage, participate in conversations, etc. Over time people will be exposed to you, your ideas, your thoughts and you will begin to see your network grow. You really need to throw your ego completely out the window for this one. When enough time passes you will see that people actually start reaching out to OFFER you job opportunities.

Asking for advice is different from asking for a job

My next article will probably be titled “The Art of the Private Message”, because there is much to say on how your messages are interpreted by the receiver.

I do want to emphasize one thing. I personally have a soft spot for people who reach out to me to ask for advice. “How do I get into this field?” “How should I start out learning data science?” “Do you think I should do a bootcamp, or is self-learning enough?” “Could you tell me a little bit about how you made a career change and the challenges you experienced?” These sorts of questions are very different from “Hi Inna, I’m Bob, here’s my CV, please pass it along if you find it interesting.”

When someone messages me and asks for advice and wants to meet with me to try to resolve some questions they have about the field, 9 out of 10 times I take a meeting with that person. I want to help. Asking me to chat with you about data science, product management, your career goals, or anything else along those lines is a fantastic way of helping me get to know you. Asking me to do something for you which involves me putting my own reputation on the line before I’ve even met you is a bit much.

When you private message people and ask for meetings, I would still combine this strategy with the tips above. I would also make sure your message is polite and well crafted, so that you increase your chance of getting a response (look out on future posts about this).

Start Practicing!

I miss attending in person talks by CTOs of tech start-ups as much as the next person. I miss meeting other data nerds and grabbing a drink and bonding over our data science experiences. Nevertheless, over this past year, I have met some extraordinary people. LinkedIn has allowed me to regularly interact with people from different countries, different time-zones, industries I was completely unfamiliar with. I have learned so much, but I have also made many friends. We exchange book recommendations, bond over our extracurricular activities, make plans about meeting in person one day. It has been an extremely enriching experience, and I hope you get to have it too! Don’t think too much about it, just start building your LinkedIn network NOW.

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Inna Saboshchuk
DATAcated

Research psychologist, turned data scientist, then data product manager in retail. My passion is democratizing data and helping you reach your goals.