How to Network as a Data Scientist

The reality of the data science job market in 2024
It’s no longer as simple as sending your resume to a few companies and getting interviews two weeks later.
The battleground for Data Science jobs gets more intense by the day. In my last article I described the challenges that data scientists are facing in 2024 and one of them is the competitive job market.
In this last post I ran a quick LinkedIn experiment which showcased how narrow the job prospects can really get when you add basic filters like "full time" and "remote".
I have had many juniors and aspiring data scientists reach out to me and comment on my articles, asking for advice on how to get hired in the current climate.
I always tell them that networking is key because simply smashing the easy apply button on LinkedIn (especially if you don’t have a ton of experience yet) is unlikely to get you hired at the companies you really want.
So in this article, I want to discuss two major ways of networking (Online and In person) and how data scientists can best connect with others and land jobs in 2024.
Online

LinkedIn is the holy grail of professional networking and learning how to properly use it to your advantage is extremely important.
There are two main areas you can improve on when using LinkedIn:
- Breadth: Increasing quantity of connections
- Depth: Messaging connections and increasing quality
Maximizing connections
It’s obviously important to get lots of connections — the larger your network, the more potential opportunities for finding work.
But it’s equally important to maximize the quality of connections you’re making.
Here are some LinkedIn connections to prioritize:
- Alumni who went to your university or current students. Prioritize those who are studying or have studied data science or a related field.
- People from your current company. Even **** if they are in a different department or country, connect with people working in your same role or in related roles (data engineers, software engineers, ML engineers, BI analysts, etc).
The main takeaway is to prioritize making as many connections as possible with people in the data science community, people who have careers in data science and work on data teams, and people who you can connect with and find common ground with (for example, people who also went to your university).
Now that you have a plethora of good connections, it’s important that you stay active and alert on LinkedIn. Check the app regularly — daily if you can. This way you can see who’s hiring, who made a recent post you can comment on, and find more engagement opportunities.
When you find people who are hiring, or who are working at a company you’re interested in, the next step is learning how to reach out and actually get results.
Crafting the right LinkedIn message
I get many messages on LinkedIn from aspiring data scientists. Because I am a busy individual, I don’t respond to most of them.
In an ideal world I would give everyone a job, but in reality I only have so much time in a day to help people out for free.
The types of messages I usually get are along these lines: "Hi, I saw that your company posted a position for a data scientist. Can you please refer me?"
This is NOT a good way to reach out to people for networking and job opportunities!
This is what you want to include in a LinkedIn message:
- Polite introduction. Say hello, hope you’re doing well, my name is, etc.
- Introduce your background. It’s best if you have domain specific experience or interest. For example, if applying to an energy company, even mentioning you have a minor in Sustainability, or that you took a class on Renewable Energy, can help you stand out.
- Use proper grammar and articulate yourself professionally.
- Don’t ask for a job or referral right away. Simply express interest in the work that the individual you are messaging is doing. You and the person you are messaging can get to know each other a bit better, and most likely they will offer to refer you (If not, then you can ask).
This is an example of a good message I received on LinkedIn, which I responded to.
"Hi Haden! I saw that you’re a [University] alum working as a Data Scientist at [Company Name]. I’m a Data Science and Environmental Sciences student at [University] and I’d love to learn more about the Data Scientist position. I’m hoping we can connect!"
Notice how he did not ask me for a job. He didn’t ask me for a referral. He simply introduced himself, stated his background (that he is a student, what his degree is) and expressed interest in our data science posting.
What stood out about him also, is that his degree of study was related to my company’s domain (energy and environmental sustainability).
I did end up referring this person for a job at my company. Unfortunately, because we ended up hiring internally, it didn’t work out. But what matters is that he gained a huge advantage by sending me a good LinkedIn message.
Medium & Technical writing
In the past year or so I’ve written over 20 articles on data science and technical topics. I’ve built a following of mostly data science interested people and have gained many great connections on LinkedIn.
My Medium page has generated a lot of new traffic on my LinkedIn especially when I write an article for Towards Data Science and they shout me out.
Anyone who reads my data science technical articles is able to see my Python programming skills, read about my experience in data science and observe my writing and communication skills.
These articles are a great supplement to my resume and serve as a portfolio in and of themselves.
One of my coworkers who had me on LinkedIn read one of my articles about Bayesian Optimization and reached out. He invited me to present on the article at our company’s online data science seminar where over 100 people from my company attended. I surely gained some great LinkedIn connections and other contacts from that!
So if you’re a writer like me and enjoy writing technical/data science articles, I do recommend you start writing on Medium! Write your own articles, follow other data science writers, comment and engage with other articles and leave your LinkedIn in your bio or add it at the end of your articles.
In person

Networking shouldn’t be limited to just online. There are plenty of great opportunities to network in person. And if you can manage to do it, it can be even better than online because making a face to face impression allows you to communicate better and makes you much more memorable.
Some tips for making in person connections:
- Events. Look for data science events in your area. Conferences, talks/presentations, workshops, classes, etc. A lot of times workplaces will host data science conferences as well so look into that and sign up!
- Friends and family. Don’t **** underestimate your friends, their friends, your family, your family’s friends, your friend’s family… you get the picture. Make sure that your friends and family know that you’re a data scientist and don’t be afraid to ask them to let you know if their company or anyone they know is hiring. Also, don’t be afraid to reach out to old friends if you see them post something on LinkedIn or other socials that may be data science related. Recently one of my old college friends posted about her healthcare analytics startup. I reached out, congratulated her on her work and let her know that if she ever needs a data scientist to give me a call!
- Strangers. If **** you like to be adventurous once in a while and chat with strangers, you should ask them what they do for work and let them know what you do. You never know who might be in the field. I met a guy standing in line at a pizza shop. We exchanged LinkedIns when I found out his company was looking for data scientists.
Conclusion
Networking is a valuable skill that will absolutely put you ahead of most people who are sitting at their computers all day clicking apply.
Although data science is a highly technical field there will always be a human aspect to getting hired because humans are the ones doing the hiring.
Knowing how to be friendly, professional, approachable, social and respectful goes a long way when it comes to getting a good job. These skills are showcased when you can effectively network with people around you.
If you can really master the art of networking you will always have a huge edge in the job market.
Thanks for reading
This article wouldn’t be complete without a link to my own LinkedIn:
https://www.linkedin.com/in/hadenpelletier