Are you ready to become Data Scientist and Stand Out?
Are you ready to become Data Scientist and Stand Out?
Be a star on your own!
Hello Everyone!
Happy day to you all, and I wish you all the best in your learning and career😊.
Here are a few tips to stand out as a data scientist.
Whether you are trying for job interviews or a professional, these tips are for you!
Expect 4 min readings, so enjoy the reading.
In this article, I want to discuss how you can stand out in your career and the employer's eyes via certain activities.
Data science is dubbed the sexiest job in modern times, and the sentiment attracts many people to get into the field.
It becomes harder to stand out from the others as many people have a similar skill set.
How to differentiate yourself as a job seeker and a data scientist?
Here are 3-step plans you could do👇👇👇
Step 1. Share your voice on Social Media
Let’s start by sharing your experience and learning journey with the world.
Your journey is uniquely you, but everybody loves to know someone who got through the same experience. Why? Because it is relatable to them.
Sometimes we don’t know what to share and have a brain freeze. Here are some great ideas I know have proven to attract many viewers:
Sharing your mistake experience
Nobody is perfect, and your data learning journey could be full of learning mistakes and missteps.
However, everyone can learn from someone's mistakes. What you have shared might prevent someone from repeating your fault.
Share your accomplishments
On the other spectrum, almost everyone is happy to see someone succeed and their life because it inspires them.
Every accomplishment creates a new chain of success where the person who read your success would think that they too could achieve what you have.
You don’t need to start by sharing a big moment. A small success such as understanding Python iteration or successfully creating your machine learning model is an inspiration for everyone.
More people need your voice than you ever know.
Share simple tips you know.
Maybe you know how to learn data science more efficiently, or you know a new Python package that could help data science work easily.
A simple tip might be something you feel is unimportant, but you never know. There is always that person who needs your knowledge.
Share Article/Learning Materials/Someone Else Post
You come across a great article or post, and you learn a lot from that. Great! Now you could share the same material with the other.
Everyone is benefitted from the knowledge you share and how great the feeling is when someone says thanks because of your sharing.
Someone might need to read this article as well! You could help them stand out together by sharing my article👇👇👇
Step 2. Write Write Write Consistently
You have shared your thought on social media but don’t let them become a one-time gig.
Create a system where you are comfortable with writing and can keep your content produced consistently.
Writing consistently needs preparation, and I would share some tips and tools you could steal!
Determine your writing medium
Your writing medium is important because you would spend most of your writing them there.
Find the one you enjoy the most—Medium, LinkedIn, Substack, Twitter, etc.
Just make sure that your audience can reach out to you.
I started writing on Medium and moved to LinkedIn. Creating by those two platforms for me is already enough to garner attention—which I am sure everyone could do as well.
Create writing system
Writing consistently is not something that could happen overnight, but it could be trained.
To make things easier, you could utilize these various tools to help create a writing system:
Notion.so to help you structure your content and templates
Buffer.com to help you schedule your content publishing
Canva.com to prettify your social media account and writing
Carbon.now/ray.so to create a beautiful code image template
Grammarly.com to help your grammar correct
These five tools are already enough to make a writing system, as long as you did it properly.
Creating the proper system for data science writing and content could be hard. I would share my system experience in my future writings, thou you might be interested in subscribing to my future writing.
👇👇👇
Step 3. Create an Online Portfolio
What is data science without a project portfolio? Well, still a data scientist but without proper exposure to their work.
It is easier than ever to create an online portfolio that your future employer or audience can access in modern times.
You might already have the code and analysis, but you now need a place to share your portfolio with the world.
There are various tools you could have to create that nice online portfolio:
The website to create a nice free landing page. You could create a landing page for your article or your website.
Do you know if you could create a website directly from GitHub repositories? If not, then try out the GitHub Page.
What better ways to share a data analysis and machine learning model by using a data app? Streamlit provides a simple yet elegant way of data app creation.
You may be a more coding person and love to build your website but need a free place to host it. Heroku is there to help you host the data science portfolio.
If you create your data science analysis using R, you can utilize the portfoliodown package to make the data science website.
Is there something that I miss? Be part of the discussion and leave any comments below 👇👇👇
That's all for this today! Simple tips to make you stand out as a data scientist
If you enjoy this newsletter, the best compliment you give me is by saying something nice about my article online.
I always appreciate hearing that people enjoy my newsletter.
See you again next week.
Cheers,
Cornellius