Data science has evolved to become an invaluable and indispensable field in today’s context as it is being used by leaders across a wide range of industries. Executives understand the importance of gathering, analyzing, and interpreting the vast chunks of data that is produced by all organizations on a daily basis. Data has become part and parcel of our lives. Answering the question, ‘Is data scientist the most promising job?’ the obvious answer is a ‘Yes.’ The technological revolution has created plenty of opportunities for both budding, mid-level, and experienced data scientists.
What is Data Science?
Data science is a blend of various algorithms, tools, and machine learning principles that operate with the goal of discovering hidden patterns from raw data. It is used to make decisions and predictions by using prescriptive analysis, predictive causal analysis, and machine learning. It is used to scope out the right questions from the dataset. It is a multidisciplinary field that works at the raw level of data (structured, unstructured, or both) to make predictions, identify patterns and trends, build data models, and create more efficient machine learning algorithms.
Enterprises have started employing data scientists for performing critical research such as sales forecasting, market analyses, business analytics, and anticipating labour demands.
Why is data science currently the most promising job?
There is a severe shortage of data scientists at a global level. The Bureau of Labor Statistics (BLS) has predicted that there will be a 30% growth in the field of data science in the decade that precedes 2026. The top reason for this growth is the government and business adoption of big data systems. Analyzing big data helps enterprises achieve their objectives.
Remarkable achievements such as machine learning and artificial intelligence are helping data scientists achieve even more, and there is a constant need for humans to direct, monitor, develop, and adjust highly advanced data analysis programs. Nowadays, due to the growing need, companies are giving more importance to data science certifications and industry expertise than a background in computer science.
Proven Steps to Land the Right Data Science Job
Some of the proven steps to secure a data science job are:
1. Customize Your Resume
Though your resume might have gone through multiple revisions, it is important to customize your resume. This is because there is no such thing as the best resume, as you can always get better. Resume customization must incorporate an understanding of the target role and the branding message. The ultimate goal is to develop a resume that resonates with the employers since you will always present yourself as the perfect candidate they are looking for.
2. Revamp Your Online Presence
Nowadays, it is very rare that an employer will not look up your name on the internet after you attend the interview. Linkedin is the most used tool in the professional world. Thus, being on Linkedin and having an attractive profile is not a choice anymore, but a necessity. What is most important is to have a strong and relevant Linkedin profile. If you are applying for the role of a data scientist, you must make sure you add details such as your skills in programming languages such as Python, R, and SQL. If you are applying for a machine learning engineer’s job, you can swap the SQL skillset with Java or C++and add machine learning model productionizing experience.
3. Define a Clear Target Role
If you do not have a direction, any direction is the right direction. As far as the job search is concerned, the target role is your direction. Pursuing the right target role will lead you to a better interview experience and application response rate given the good match between your profile and the target role’s ideal candidate profile. So, it is important to research the requirements while applying for each role and find out the best match in terms of education, skills, and experience.
4. Make a Systematic Action Plan
It is often said that job-hunting itself is a full-time job. The first step is to identify the activities we need in the job search and map them out on a daily basis. This refers to activities such as networking, data science projects, online applications, practising data structures and algorithms, interview preparation. This way, you will be able to spend most of your time on a job search. When everything is done according to plan, and in a systematic manner, you will have greater chances of moving closer to the final goal- a job offer.
Conclusion
Given the demand for data science jobs, the competition for data science jobs is only increasing. But while trying for a data scientist’s role, it is important to understand that bagging a data science job is a frustrating and long process of job hunting and interviews before landing a satisfying opportunity. But it is important to understand that your job search is also a learning process. Though it is a challenging industry to break into, the rewards are well worth the effort.
To know more about data science certifications, check out Global Tech Council.
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