Ian Klosowicz
Networking doesn't have to mean walking into a room of strangers and handing out business cards. For most aspiring data analysts, the version that actually works looks nothing like what you've been told. You don't need to be an extrovert, go to meetups, or "build relationships" with people you met for 6 minutes at a conference. You need a handful of real conversations with the right people, and most of those can happen online.
Most networking advice was written for salespeople.
"Work the room." "Always be closing." "Your network is your net worth." That's advice for someone trying to close a deal, not someone trying to learn if a company is worth applying to.
The problem isn't that you're bad at networking. It's that the advice you've been given describes a version of networking that makes most people feel like they're performing. Fake energy. Forced small talk. Immediate pivots to "so, what do you do?"
That version is also mostly ineffective for job seekers.
What actually works is much simpler: find people doing the job you want, ask them genuine questions, and stay in touch with the ones you connect with. That's it. No script. No pitch deck. No business cards.
I've watched thousands of aspiring analysts go through job searches. The ones who got hired fastest weren't always the most technically skilled. They were the ones who had conversations with people inside companies before applying.
Good networking for a job search comes down to 3 things:
None of these require you to be outgoing. They require you to be consistent and genuine.
The math is simple. If you apply to 50 jobs cold, you might get 3 callbacks. If 5 of those 50 applications come with a warm referral or an internal advocate, your callback rate on those 5 goes up significantly. Even 1 or 2 warm connections can meaningfully change your outcomes.
LinkedIn is where most data networking actually happens, and most people do it wrong.
The typical message looks like this: "Hi [Name], I'm trying to break into data analytics and I'd love to pick your brain. Would you be open to a quick chat?"
That message gets ignored 9 times out of 10. Not because people are rude, but because it's vague and asks for something without offering any context.
Here's what works better:
A message like this gets read: "Hey [Name], I saw your post about transitioning from finance into data. I'm in a similar spot right now and I had one question about how you approached the SQL side of things during your job search. No call needed -- even a line or two would be really helpful."
That's it. Specific, short, low-commitment.
Send 5 of these a week. Don't send 50. Quality of outreach matters more than volume, and personalization takes time. The goal is a few real conversations, not a mass email campaign.
If someone responds and you have a good conversation, connect with them. Don't send a connection request as your opening move. Lead with the message, connect after.
An informational interview is a 20 to 30 minute conversation where you ask someone about their job, career path, or company. You're not asking for a job. You're gathering information and building a relationship.
Most people undersell how useful these are. They also make them awkward by not having good questions ready.
Questions that work:
Questions that don't:
After the conversation, send a short thank you message. Not a novel. 3 to 4 sentences. Thank them, mention one specific thing they said that was useful, and say you'll stay in touch. Then actually do it.
When I was transitioning into data, I didn't have a single contact in the industry. Every person I eventually knew in this field came from reaching out cold to people I found online. Some didn't respond. Enough did that it changed things.
The hard part isn't starting a conversation. It's maintaining it.
Here's a low-pressure system that works:
You don't need to check in monthly on a schedule. Just be present in a way that feels natural. The goal is that when you eventually reach out and say "I'm actively interviewing right now," they remember who you are.
The people who get referrals aren't always the most qualified candidates. They're the candidates the employee already knows something about.
Start with communities, not individuals.
The strategy isn't to lurk. It's to participate. Ask questions. Answer them when you can. Share what you're working on. Over time, people start to recognize your name, and that makes the one-on-one outreach significantly easier.
One thing I tell people in Analyst Hive: if you've posted on LinkedIn 0 times, getting a referral from someone you've never met is a longer road than it needs to be. A public presence, even a small one, gives people something to look at before they decide whether to respond.
If you're trying to break into data while employed somewhere else, your current company might be a better launching pad than you think.
Internal moves are often easier than external ones because the trust is already there. And even if your company doesn't have the role you want, the people you work with now have networks too.
I work in data engineering today. Snowflake, Coalesce, pipeline architecture. I use it every day. And a meaningful chunk of what I know about how data teams actually operate came from conversations I had with people in other departments, not from documentation or courses. The informal conversations are where you learn what the job actually looks like from the inside.
How many people should I reach out to per week?
5 is a solid target. More than that and the quality of your messages starts to drop. Less and you won't build momentum. The goal is consistency over time, not a single burst of 30 messages you send once and never follow up on.
What if no one responds to my LinkedIn messages?
Check the message itself first. If it's generic, vague, or long, rewrite it. If you've sent 20 specific, short, genuine messages and still have 0 responses, shift your audience. Try people who are more junior in their careers, who post publicly about similar topics, or who are part of the same communities you're in.
Do I have to go to in-person networking events?
No. In-person events can be useful but they're not required. Most of the meaningful networking for a data analyst job search happens online. If you're an introvert, lean into written communication. You're probably better at it than you think.
Is it weird to reach out to people I don't know?
It feels weird the first few times. It stops feeling weird after that. Most people who've been in your position are genuinely willing to help because someone helped them. Keep the ask small and genuine and most reasonable people will respond positively.
What if I don't have any projects or skills to talk about yet?
Start building something. A portfolio project, a SQL practice log, anything. You don't need to be polished before you start talking to people, but having something you're actively working on gives you something to talk about. "I'm currently working through [X]" is a better conversation starter than "I'm just getting started."
When is the right time to ask for a referral?
After at least one real conversation where you felt a genuine connection. Not on the first message, not right after the first call. Give it at least a few weeks and a couple of exchanges. Then be direct: "I noticed [Company] has an opening for a data analyst. Would you be comfortable referring me, or at least letting me know if it's the right fit?" Most people appreciate the directness more than another vague ask.
If you're working through a data analytics job search right now, the job search mechanics are one piece of what Analyst Hive covers. It's a program on Skool built around daily tasks that take you from zero to interview-ready: portfolio projects, LinkedIn setup, application strategy, and interview prep. The networking piece is baked in throughout Month 2. Join the community.
