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Top Habits For Data Analysts To Help Them Become Successful Data Scientists

Top Habits For Data Analysts To Help Them Become Successful Data Scientists

Rohit Yadav
Top Habits for Data Analyst

Data analytics might be the first step for you to follow to pursue a career in data science, but transitioning into a data scientist is not that straightforward. The skills required to become a data scientist is more demanding. While data analytics techniques may act as a foundation, you need to develop effective habits to expedite the learning process and become data scientists.

Here are key habits that will help you pick up the required skills to quickly become a data scientist:-

Continuous Learning

The leap from a data analyst to a data scientist can only be accomplished if one continuously learns new techniques. While learning can happen in the office as well as outside working hours, it is recommended to learn in a structured way by enrolling in advanced data science courses. “Working professionals can self-learn, but they should utilize the time effectively by opting for numerous structured courses that are hosted online,” says Pavan Kumar Thatha, Emerging Technologies Leader at Unisys. “Unlike students, professionals can afford the money to save time and learn quickly.”



A data analyst will not only have to learn various machine learning and deep learning techniques, but master them as well. Consequently, they must adopt guided learning if they want to quickly become data scientists.

Teaching

Learning is essential for growth, but at the same time, data analysts should share their knowledge through LinkedIn posts, blogging, and teaching. Communicating what you are learning helps others learn from you and ask questions. This will assist you in researching further to answer readers’ questions, resulting in enhancing your knowledge in data science techniques. “Teaching is the best way to learn data science skills,” said Anand S, CEO at Gramener. 



Besides, teaching also increases your storytelling skills, which is an important skill for data scientists to obtain as their day-to-day work involves explaining the outcomes to stakeholders and other non-tech experts. Storytelling is often evaluated in interviews, so mastering teaching skills increases your chance of landing a job. Also, it will be effective while you are working as data scientists to communicate technical knowledge across several departments easily.

Talking To Data Scientists

In the ever-increasing data science landscape, you cannot learn everything. Thus, you should have mentors who can shape your career. Being in touch with prominent data scientists is as vital as learning technical skills. Data scientists can guide you in the right path by eliminating your confusions, which aspirants often struggle to find answers to. By getting your career-related doubts clarified, you can accomplish your goals with confidence. Making a habit of spending time with data scientists helps you understand the landscape better, and in turn, enables you to choose your career path accordingly. 

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Hackathons

Data analysts should demonstrate the skills they have obtained by participating in hackathons and other platforms. While the projects that they do within the organization are self-explanatory, participating in competitions will give them exposure working with the best in the world. This allows professionals to assess themselves as well.

Continuously engaging yourself in various hackathons like MachineHack can showcase your interest in challenging yourself as well as the ability to work on diverse projects. However, just winning a hackathon or two does not differentiate you from others. You have to be consistent by showing up on most of the hackathons, since companies have adopted non-traditional ways in which they hire data scientists.

Reading Research Papers

A habit of reading research papers will go a long way in making you knowledgeable about data science solutions. The advantages of going through research papers are endless. Even if you do not understand the complete research, you will get an idea of what are the challenges that exist in the space. This will make you more informed and help you in making decisions about what can and cannot be done with data science techniques.
“One should at least set aside three to four hours a week to read research papers. Initially, it can take a month to read and understand a research paper, but it is worthwhile,” said Srinivas Atreya, Chief Data Scientist at RoundSqr.

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