In the rapidly evolving field of data science, it can be challenging to understand what it takes to be a successful data scientist. Data scientists play a crucial role in developing, implementing, and deploying machine learning algorithms to gain meaningful insights from data. They use advanced statistical methods and cutting-edge technologies like neural networks to perform predictive analytics.
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The Profile of a Data Scientist
To gain a better understanding of what makes a data scientist successful in 2019, we conducted a study to analyze the typical data scientist profile. Here are some key findings:
- Gender and Language Skills: Currently, the field of data science is predominantly male, with 69% of professionals in this domain being men. Proficiency in multiple languages is also a common trait among data scientists.
- Experience and Education: On average, data scientists have been in the workforce for 8 years, with 2.3 years specifically spent working as data scientists. Additionally, 74% of data scientists hold a Master’s or a PhD degree.
- Programming Skills: Programming skills are essential for data scientists, with 73% of them being proficient in both Python and R. Other valuable programming skills include SQL and MATLAB.
- Academic Background: Data scientists come from diverse academic backgrounds. While degrees in data science and analysis are relevant, degrees in economics, social sciences, natural sciences, statistics and mathematics, computer science, engineering, and even law can lead to a successful career in data science.
- University Ranking: Contrary to popular belief, the ranking of the university you attend does not significantly impact your chances of becoming a data scientist. While many data scientists come from top-ranked universities, a significant portion also come from universities ranked outside of the top 50.
- Online Courses: Online courses play a vital role in the education of data scientists, with 43% of them having gained at least one certificate from an online course. E-learning platforms offer valuable resources to help data scientists master programming and data handling skills.
Programming Skills: Python Leads the Way
When it comes to programming skills, Python is the most widely used language among data scientists in 2019, with 54% of professionals working extensively with it. R is the second most popular language, although its popularity varies by location. SQL and MATLAB are also considered valuable skills for data scientists to possess.
Industries That Employ Data Scientists
In terms of industry, the tech and IT sector remains a major employer of data scientists, accounting for 43% of the workforce. However, the industrial sector is rapidly catching up, employing 39% of data scientists. The financial sector is another significant employer, with 16% of data scientists working in this industry.
Career Progression: Location Matters
Those looking to advance their careers quickly in data science should consider locations like India and the UK. These two locations offer opportunities for data scientists to thrive even with little to no experience. In contrast, the United States prefers data scientists with 3 to 5 years of experience for career progression.
Conclusion
Becoming a successful data scientist in 2019 requires a diverse skill set, including proficiency in programming languages like Python and R, advanced statistical knowledge, and a strong educational foundation. While a Master’s or PhD degree is often preferred, practical abilities and the ability to learn on the go are equally important. Remember that the field of data science is constantly evolving, and staying updated with the latest technologies and methodologies is key to success.
If you’re interested in embarking on a career in data science and need a comprehensive preparation, visit our website Techal to explore the resources and courses available.
