5 Ways Data Scientists Can Transition Into Managerial Roles
It is no surprise that data science today has become the backbone of several organisations across the globe. From the core to the edge, a lot of organisational decisions are based on data science. With time the job role of a data scientist is just becoming wider and talks about T-shaped data scientists is gaining ground. However, even though the domain has experienced a major boom, it is fraught with its own unique set of challenges, and now, it is experiencing a shortage of top talent for specific job roles such as Data Science Manager. But why is it happening? To answer this question, we will have a look at the reasons why Data Science domain is witnessing a talent crunch for DS managerial roles and how one can become a DS manager. The Need For Data Science Managers A lot of students are taking up data science courses to start their career. That is not all, a lot of professionals from other domains are also making the transition and taking up data science as the career path. And why no — it is one of the highest paying jobs. But now this boom is posing a huge challenge to a lot of companies across the world. While the number of data science professionals is increasing, the number of managers are still the same. The companies were not realizing this lately, but now they are actively looking to onboard DS managers. Having a strong data science team is one thing, but if you don’t have a manager who is goal-oriented, cares for the team, actively listens to them for making decisions, is a mentor, and empowers and inspires team members, then the efficiency of a data science team decreases. Now you must be wondering that if it only takes leadership skills then why companies are not hiring managers from other domain? The reason is that a DS manager along with leadership skills need to have advanced knowledge of data science — if s/he lacks that knowledge how they are supposed to lead a team of data and analytics professionals and implement data science solutions? In order to cope with these challenges, many organisations have started training and promoting the leading data scientists to managerial roles. And it is turning out to be one effective solution. So, if you are also planning to make a transition, then along with all your data science skills and knowledge you need some of the other skills. Here Is How One Can Make A Transition Into DS Management Role 1) Build A Know-How Of The Data Science Domain One cannot be a leader without knowledge of the field, and data science is no exception. To be a data science manager, you need to have in-depth knowledge of the data science domain and a significant amount of experience, as you would be leading a data science team with people having different skills. If you are working as a data scientist and lack certain skills and concepts, make sure you seek help from your fellow data scientist. 2) One Cannot Jump Directly To A Managerial Post. Get promoted, First! This is something you all have to accept that one cannot directly make a transition into a managerial role — there are certain criteria that need to be followed. And one of the criteria is to get promoted to posts such as IC, lead data scientist etc. This would give you a platform to perform for a bigger picture. When your work gets recognized, you get promoted and that means, you are one step closer to your goal of becoming a manager. Word to the wise: Even though you get promoted to a different role, do not stop your data science learning process. 3) Start Developing Leadership and Mentoring Skills When reaching a certain position as a data science professional and gain a significant amount of knowledge, try to help fellow data scientists or the juniors. There is nothing wrong in proactively asking your juniors if they require any help in solving critical data science problems. This might require extra hours, but considering the perk that is completely okay. The more you share your knowledge the more you gain. If you are a lead data scientist, make sure you correct your fellow employees in a manner that they don’t feel you are being a boss. There is a huge difference between being a boss and a leader and once you master that sorcery of being a leader, the chance of you becoming a manager increases. 4) Connect and Network With Other Leaders In The Company This might sound political, but it is not. Connecting with higher management doesn’t make you a desperate person to get a promotion, rather it helps you understand the company’s processes better. A person from the higher management would definitely have more experience and knowledge than you and once you start conversing with them you start getting a clear view of how to pave your path towards becoming a manager that not only leads a team but also empowers and inspires. 5) Go Through Management Assessment Almost every organisation follows the policy of Corporate management assessment. This is a process where the potential candidates are assessed thoroughly — whether it’s their leadership skills, mentoring skills or core knowledge of the domain. So, when you are provided with the opportunity to go through this assessment, make sure you take things seriously and perform well. Make sure you do your homework well on all the aspects that a data science manager need to cover.
It is no surprise that data science today has become the backbone of several organisations across the globe. From the core to the edge, a lot of organisational decisions are based on data science. With time the job role of a data scientist is just becoming wider and talks about T-shaped data scientists is gaining […]
Here, we will look at the reasons why Data Science domain is witnessing a talent crunch for DS managerial roles and how one can become a DS manager.
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