How do I Move from Data Scientist to Data Science Management?

Data Science has become the backbone of industries across the globe currently. Many organizational decisions are made based on data science. Data science courses are made available across the country to attain proficiency levels. The certification courses available in India are Python, PowerBI, SQL, Excel, and Machine Learning. The online and offline institutes are available to impart learning in data science courses.   The increasing demand for the data science profession among youth and professionals of other domains is because of the high salary package. This has led to a severe challenge for many companies because of the constant number of managers at the rise in data science professionals. The deficit in managerial roles was realized quite late by the companies.    A Data Science Manager is goal-oriented, looks after the team, and initiates decisions that are decided mutually. S;/He acts as a mentor and empowers and inspires team members so that the efficiency of a data science team is maintained. The role requires advanced knowledge of the data science domain with leadership skills which are imparted through online data science courses and training from organizations. 

 

Ways to make a transition from Data Scientist to Data Science Management

 
  1. Build know-how in the Data Science domain
A manager in the form of a leader requires extensive knowledge of the data science domain with a fair amount of experience. The managerial role involves making an unbiased decision in a data science team with people having different skills.  
  1. Promotion is required to achieve a Managerial post
It is not possible to directly land a managerial role from a fresher. There are some criteria to follow that may involve a degree of knowledge and a certain number of years of experience. In general, recognition of work in industry is one of the best ways to become a manager.   
  1. Develop Leadership and Mentoring Skills
Any senior at a higher level in the data science profession hierarchy will have a significant amount of knowledge, so they should proactively come forward and assist the juniors of the concerned team in solving critical data science problems. A High amount of technical knowledge shared among junior level is equally proportional to the growth of the company.  In this process, it is significant to balance the line between being a boss and a leader, and once the potential to become a master is reached, the chance of becoming a manager rises.  
  1. Networking with other leaders of the Company
Connecting with employees and leaders of other team do not reflect negatively instead it helps in understanding the company’s processes better. For instance, if you intend to engage with a leader at a higher position, it will give you a clear view to pave your path toward becoming a manager.  
  1. Go through Management Assessment
The Corporate Management Assessment policy is practiced in many companies. It is a process where the candidate is thoroughly assessed based on leadership skills, mentoring skills, or core knowledge of the domain. It is essential to consider the opportunity of a managerial role seriously and stay updated with knowledge related to data science management.  

Challenges during the transition from Data Scientist to Data Science Management

  Below we have discussed the challenges faced by a data scientist in a managerial role in brief:  
  1. The identification of a good manager is measured when he meets his team’s objectives with the company's growth. The manager role demands varied skills and activities from recruiting, communication, and coordination to directing and making decisions. There’s a high possibility of miscommunication among young managers during team meetings so, it is suggested to engage with an experienced manager beforehand to discuss significant matters. 
  2. The report created by a data science manager reflects everything. Instead of verbally explaining everything, the report should explain each section itself. Based on the project's objectives, the leader should set their priorities to feel empowered and confident throughout the presentation.
  3. Hiring is one of the significant tasks of a manager. The issue related to this process is that it is rare when compared with other management tasks. The solution to this problem is to find the technical fit, then find the team fit. It is preferred to employ a good team fit with a good technical fit than a perfect technical fit with no team fit.

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