How I Earned My First Promotion in Data Science
Practical advice to help you get promoted quicker
Earlier this year, I got promoted!
I went from a junior data scientist to mid-level. I started working as a data scientist in September 2021, so it took me about 2 and a half years to get this promotion.
I want to share some tips and advice that helped me get promoted, so you can reach the next level quicker than I did!
This is a guest post by from . Egor is a London-based data scientist and a prolific content creator. He is a top writer on Medium in DS, ML, AI, Statistics & Optimization. He runs a YouTube channel with hands-on technical lessons and career advice. I find Egor’s style humble and straight to the point.
You can also reach him on: LinkedIn, X (Twitter), or Instagram.
🕰️ Reading time: 7 mins
My journey
I want to briefly summarise my journey within data science to build some context behind my promotion.
From September 2017 to July 2021, I studied and graduated with a master’s in Physics. During my final year, I realised physics research was not for me, so I decided to become a data scientist after watching the AlphaGO documentary. It’s amazing. You should check it out!
In 2021, I proactively dedicated my time to mastering essential Python, statistics, and machine learning skills. This led me to several job offers in data — and other quantitative-based roles.
My work timeline looks like this:
September 2021: I accepted a graduate data scientist scheme with a UK insurance company, where I stayed for about a year.
September 2022: I joined Gousto, a recipe box company, as a junior data scientist (level 1)
March 2024: I was promoted to a mid-level data scientist (level 2)!!!
Right, let’s now move onto the tips and advice that helped me get promoted!
*My advice is mainly for those looking to go from junior to mid-level. Some of it may apply to other levels, but I can’t comment as I am not there yet and have no experience in those advanced levels!
1. Understand the promotion process
My most important tip is to make sure you understand how the promotion process works at your company.
You can’t get promoted if you don’t even know how it works!
Even though many tech companies have similar promotion setups, how a start-up approaches promotions will diverge from an established big corporation.
Usually, companies have internal documentations that explain the promotion process. If you can’t find it or need help understanding it, ask your manager for clarification and further contacts reach out to. Ensure you understand every evaluation criteria before the promotion cycle.
Additionally, find similar documentations that list the key competencies and skills required for each data science level. Make sure you grasp every skill required, well ahead of the promotion cycle. This way, you can take action to demonstrate existing skills and build up weaker skills for that next level.
2. Be visible
Like it or not, you won’t get promoted if people don’t know who you are.
“Doesn’t my manager know me well?” you might think.
Yes, but when it comes to promotions, people much more senior than your manager make decisions at the table.
Unfortunately, at a junior level, you are unlikely to have worked on projects with the top data science managers, Vice Presidents, and CTOs.
So how do you let the top dogs know who you are and what you’ve accomplished? You must make your work visible to them as much as possible.
I’m not saying you should just go around broadcast your daily tasks on slack every hour, or raving about your work in the coffee room.
However, you should:
Ensure your work reaches the right people.
Craft concise summaries of your findings for easy circulation.
Seize every opportunity to share your insights with a broader audience.
I understand that you might feel nervous about putting yourself out there, but remember: as a data scientist, it’s essential to be able to effectively communicate your technical work to a wider audience.
When you demonstrate exceptional communication, you’re sending the “promotion-ready” signal to senior leadership.
3. Take ownership
There is nothing wrong with doing your day-to-day tasks to a high level.
However, to make the jump from junior to mid-level, you must take responsibility and demonstrate ownership over projects and deliverables.
You want be seen as the person who is: “ in charge of X”, or “responsible for Y.”
Being seen as the PIC (person in charge) shows you can work independently, signifying you are operating at a higher level than just a junior.
How do you show ownership?
You can:
Take a proactive approach to improving current systems, processes, and models.
Always look for areas you can make better instead of waiting to be told what to do.
For instance, I demonstrated ownership by:
Taking one of our data science models and guiding the direction of this data product area.
Volunteering to run our company’s journal club, where every fortnight, a colleague presents a research paper for wider discussion.
4. Seek advice and feedback
As a junior, you are at the bottom of the knowledge and experience pyramid.
To advance your career, you should take feedback from seniors and mentors within your team.
The best part about mentorship at work, is that you are getting paid to learn!
Here are some examples of how I requested feedback:
If I did modelling -> I would ask a data scientist to review
If I did analysis -> I would ask a data analyst to review
If I wrote production code -> I would ask a software engineer to review
If I wrote a business case -> I would ask the product manager to review
Be a sponge, absorb as much as you can, and iterate through each feedback.
Day by day, you will be inching closer to that next level.
Another helpful strategy: I asked colleagues who recently got promoted from my level for their suggestions on things I should improve on.
Don’t be shy. Getting advice from someone who was just in your exact position is incredibly powerful
5. Invest in technical skills
From junior to mid-level, a big part of being a data scientist is improving your technical abilities.
Depending on your company and role, I recommend investing your learning efforts in the technical areas most applicable to your job. This strategic focus will not only enhance your skills, but also align your professional development with your company priorities.
For example, the team I’m in is focused on forecasting and optimisation, so I spent a whole year learning and upskilling in these two domains. I wrote many blog posts and did several side projects to ensure my foundational knowledge in these areas was up to scratch.
Now, I’m way more knowledgeable in those two areas than I was before.
The objective to invest in technical skills is to develop your abilities to work independently, which demonstrates you’re performing at a higher level than junior.
6. Track your achievements
To ensure your promotion case is as complete as possible, log and track all your achievements, no matter how small they may seem.
Your achievements can range from a massive model improvement to a presentation to stakeholders.
Record everything. You never know when you may need to refer to it at a later date.
You can do this by creating a Word or a Google doc to fill out at the end of each week. Note down what you did, how you did it, and any feedback you got. If people tell you how great your work is, write it down! A list of testimonials will make you stand out and strengthen your case at the promotion table.
I can’t tell you how helpful my document was for my promotion case. I may forget many things I did several months ago, but my document never will.
Closing thoughts
I hope I’ve given helpful guidance on how to better structure your promotion case and get to that next level quicker, in short:
Understand the promotion process
Be visible
Take ownership
Seek advice and feedback
Invest in technical skills
Track your achievements
Remember: You need to demonstrate you are already working at the next level.
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This blogs will helps newbie in data scientist .
This is so great, it will be really helpful for up and coming data scientists looking to progress quicker