Self Evaluation – Making the Right Decision to Be a Data Scientist
The Data Scientist, Data Manager, Statistician and Data Analyst are the most popular career paths. Now, top universities have introduced courses in Data Science, due to the popularity of jobs in this field. People are drawn to the data scientist profession without analysing the responsibilities of the job, positive attitude, business and technical skills. Those who simply jump into this profession for being it very lucrative without acquiring the right skills and qualifications, they experience lots of troubles in the long run. For a clearer image of the data scientist role, in order to judge if their personality is suited, you must also assess your industry experience. It helps you figure out what exactly are your most sellable skills that are required by various employers.
Before you start pursuing different job opportunities in the field of Data Science, you may evaluate yourself to ensure that you are a qualified candidate. Listing down your own qualifications and expertise will help you a lot. Also browse through the job descriptions you want to apply for and find about the environment of the workplace. After you have listed all these details, you can easily prepare to present yourself in the best manner.
Few Steps for Self Examination
If you're not comfortable with these duties then perhaps reassess your career goals and reconsider if data science is the job for you, as these are potentially difficult duties, with a high level of responsibility for someone who is prepared for the role. Hence this is the best time and great way to evaluate whether you have made the right decision to opt the field of Data Science or not.
Data Science Brings Greater Responsibilities for Scientists & Engineers
In 2012 Data Science was the “sexy” profession but now Data Science involves a range of new duties and responsibilities which require analysis that can be positive, but still involve a high amount of work such as:
Find the Most Suitable Workplace
If you're beginning, be careful about your choice of workplace. Take some time to find the workplace which suits you and provides you with a context to learn and improve your skills. Do some research on the firm online and study what they offer, and any data about their company, whether related to business or financial matters. A firm may claim to offer “excellent engineering” but inefficiency in data use, then they are unsuitable, and you need to find another firm. This is the opportunity to search for another mentor. The best teams are the ones supported by Finance and Operations (with some knowledge in data and variance) and avoiding teams are sponsored by Engineering or Marketing (without knowledge of data usage efficiency).
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