Junior Data Scientist: The Next Level

There is a difference in the level of experience compared to Junior, Mid-Level, and Senior Data Scientists. This article will go through the expectations for all job roles and what is required to move up the ladder.

When you search online, most people advise you to stay at a Junior level for a few years before you consider transitioning or moving onto another role. There is a difference in the level of experience compared to Junior, Mid-Level, and Senior Data Scientists. This article will go through the expectations for all job roles and what is required to move up the ladder. 

Junior Data Scientist: The Next Level
sol via Unsplash


What level are you?

Most people will look at the Data Scientists' skills, years of experience, level of education, expertise, management skills, and more. A good understanding of how to differentiate the difference between the different levels of Data Scientists is the understanding of how long you can leave the Data Scientist alone to complete/handle a task without having to check in on them.

Using the analogy of “how long you could leave someone alone to complete/handle a task without checking in?”, we can break the different levels as follows:

  • Junior Data Scientist: You will typically check in daily, or maybe twice a day. They will do a lot of pair programming with Mid-level and Senior Data Scientists. 
  • Mid-level Data Scientist: You will check in with them weekly or a couple of times a month, however, they should be capable. They will also undergo pair programming with Senior Data Scientists, and advise and guide Junior Data Scientists if required. 
  • Senior Data Scientists: There is no need to check in with them as they are fully capable to deal with the task themselves. 

Although people's experience and skill level are important, it’s the level of knowledge and experience one possesses to be able to get things done. A Junior Data Scientist may reach a point where they are blocked and have no idea of getting past it, without consulting with a senior. A Mid-level Data Scientist may also face difficulties, however, they will have a better grasp of how to overcome it on their own. Whereas a Senior Data Scientist has enough experience under their belt to be able to get things done. Even if this includes hiring experts or researchers, they know what is required to complete a project. 

If you are looking for a Senior job, ask yourself “how long could someone leave me alone to complete/handle a task without checking in”. You have to be completely honest with yourself, if not you will be setting yourself up for failure. I am not saying you can’t set goals and strive to be the greatest you can be. I am saying be realistic with your current level of experience to help you find the correct role, and continuously build from there. 

Junior Data Scientist: The Next Level
Scott Graham via Unsplash


How to go from a Junior to Mid to Senior?

It’s the start of the year and we’re all jotting down our plans; career or personal related. We’re all trying to smash our goals this year. For all the Data Scientists out there, here’s some advice on how you can progress your career, climb up the ladder and increase your income. 



Reflecting on the question “how long could you leave someone alone to complete/handle a task without checking in?”, it’s all based on being independent. Juniors tend to ask more questions due to a lack of experience and skills, whereas Seniors have the ability to make decisions based on past experiences. 

This should not scare you from asking questions. There is nothing wrong with asking questions, that is how you learn. If you don’t make mistakes, you don’t have to go through a learning process, and you will always remain stagnant. However, don’t be reliant on your colleagues and senior staff to direct you every time. Avoid going to them straight away when you have a question, try to figure it out for yourself. You will feel a sense of accomplishment when you understand how to fix the problem. If you are unsure of your solution, ask your manager for his/her opinion. They will appreciate the fact that you came to them with a solution, rather than just a problem.


Putting yourself in uncomfortable positions

Many great things happen when you’re in the gutter. You crawl yourself out of an uncomfortable and unfamiliar hole. Juniors typically work on easier tasks, sometimes very repetitive and boring. If you feel like you are ready, ask your manager for more challenging tasks to learn and grow your analytical skills. 

If you are successful in completing the task, your manager or the Senior Data Scientists will recognise this and push a promotion for you. 


Start thinking like a Senior 

Senior Data Scientists can handle tasks alone, not only because of their level of experience but also due to their understanding of the businesses’ goals. The majority of Junior Data Scientists tasks are isolated and the process of completing a task does not go further than it being a request. Being able to look at the bigger picture by having a better grasp of the businesses’ short-term and long-term goals will improve your way of thinking when dealing with a request or trying to solve a problem.

Senior Data Scientists make their decisions based on not only their experience but also the needs of the company to help it grow. Learning how Senior Data Scientists approach and handle problems through pair programming, weekly team builds or 1-1’s will get you in the Senior Data Scientist mindset. 


Communication and Management

These are the major soft skills for a Mid-level or Senior Data Scientist, as they will be frequently asked for advice, direction, and help to understand a problem. Many Junior Data Scientists are not required to speak to many colleagues apart from other members of the data team and their managers. 

Being able to manage a data team as a Senior Data Scientist requires good communication and management skills, to make sure the operations are run smoothly. If there is an issue with a project that was managed by a Senior Data Scientist regardless if the task was completed by him/her; they will still have to take responsibility. The Senior Data Scientist should be vigilant to identify the error before it is presented to stakeholders. 

If a Senior lacks communication, his/her operations will fall apart, and will soon realise that the workload will fall onto them due to their incompetence. Rather than having to explain to stakeholders why the outputs are wrong or why the wrong decisions were made, managing and communicating with your data team to avoid these problems is the better solution. 




"Feedback is the breakfast of champions."

—Ken Blanchard


Asking for feedback is a healthy catalyst for your self-improvement; personal or career-related. Asking your manager about your strengths and weaknesses will help you understand what’s working for you and what you need to improve on. Nobody is perfect and there are always ways in which we can better ourselves. Great players want to be told the truth because they want to keep winning!

I hope this article has helped you to understand what level you’re at and what you need to do to get to the next level. I wish you all the best in your journey!

Nisha Arya is a Data Scientist and freelance Technical writer. She is particularly interested in providing Data Science career advice or tutorials and theory based knowledge around Data Science. She also wishes to explore the different ways Artificial Intelligence is/can benefit the longevity of human life. A keen learner, seeking to broaden her tech knowledge and writing skills, whilst helping guide others.