Senior data scientist is counted among the most coveted job positions in the world of data science and analytics, across industry domains. However, that’s true, but there is a big misconception that prevails in the data science industry that a senior data scientist knows anything and everything, and that he is a master of all such concepts that exist in the data science business landscape. Although, the truth is that the learning never ends, and no matter what position you hold as a data science professional, you have to keep yourself updated at all times, and that requires constant learning.
And it’s not just about the technical knowledge that help makes an individual rise to the position of senior data scientist, but there are other vital skills that are needed to be acquired to become an experience data scientist. A few of them would comprise – leadership, emotional intelligence, communication & soft skills, networking, among others. Besides, those rising up to the senior positions are mostly certified data scientists possessing highly relevant and best data scientist certifications under their name. Therefore, we would like to recommend industry-relevant data science certifications to the aspirants.
In this article, we will be discussing the differences in the job roles of a senior and junior data scientist, their job responsibilities, and career outlook. Let’s get straight to dissecting the job role of a junior data scientist.
Junior Data Scientist’s Job Profile
The Knowledge Prerequisites
In the role of a junior data scientist, the simplest of expectations from you comprises fundamental understanding of modern-day data science concepts. You are expected to complete your day-to-day tasks alone, or with a little help from your senior peers. At this stage of your career, you possess little professional experience, and hence, the focus must be on learning new things each day at work.
As a less experienced data science and big data analytics professional, you should always be open to learning from your senior colleagues. Junior data scientists need to ask a plethora of questions producing confusions in their mind to their senior counterparts while at work so as to elevate their career growth.
In the position of a junior data scientist, your primary job responsibility is to work on the tasks assigned to you by the senior data scientists. In case, you need some sort of an assistance while facing a work-related problem, senior counterparts will always be there for you to help.
A Data Scientist’s Job Profile
After you gain some relevant experience as a junior data scientist, you get promoted to the position of a data scientist. Here are the knowledge requirements, skills, and day-to-day work responsibilities associated with the role.
The Knowledge Prerequisites
At this stage of your data science career, you are expected to have a firm grasp on the fundamental techniques and concepts of data science. However, it doesn’t translate to you knowing everything associated with the industry domain of data science and big data analytics. Rather, it pertains to you knowing a lot of things, but at the same time, also knowing what you don’t know, and in which direction you need to work hard on yourself. By the time you reach to this level, you would have gained enough practical experience.
The learning doesn’t end no matter what stage you reach in the data science domain. And hence, you are still very much open to new approaches and ideas. As a data scientist, you ask many questions to your superiors at work, while also get asked numerous questions by your junior counterparts. You still learn new things on the job, but not as frequently as a junior data scientist would do. You push yourself towards acquiring a deeper understanding of certain tools and techniques used for data analysis.
You are now a contributor to the decision-making process in the company’s data science projects. You now understand the context and complexity of the projects but then you are not required to lead the projects, and the role must be limited to providing strategic inputs.
Senior Data Scientist’s Job Profile
Ultimately, after gaining several years of experience working as a data scientist, you are promoted to the coveted position of a senior data scientist. This role provides you with more power and authorities when it comes to leading a data science project. Also, by now, you must have become a certified data scientist, as most professionals reaching this career stage, get equipped with multiple big data credentials.
Let’s discuss the said role in brief.
The Knowledge Prerequisites
By now, you are already an expert at the various techniques and concepts used for executing on a range of data science projects. Also, you are aware of the potential pitfalls that might come your way, if things do not go the way you have had planned. You sourced this extensive knowledge & skillset while working for years on a variety of data science projects. With this much of professional experience under your belt, you can easily take on to any kind of a big data project.
At this level of hierarchy, you already have a strong grasp on the fundamentals of the subject, and hence, you go for learning the most advanced concepts in data science that are industry-relevant in the contemporary times.
Day-to-Day Work Responsibilities
You lead the data science projects at your firm. Now, you are just not the input-provider in terms of project strategy, but the leader, and the decision-maker. The responsibility of making the project, a success, lies on your shoulders. Also, your leadership style determines the happiness quotient of your team upto a certain extent. Alongside leading projects, you are also made responsible to converse with the outside world, and bring in some great clients for the firm you work for.