Data Scientists Need These 8 Skills
The growing demand for data scientists offers an appealing career path for both students and current professionals. Those who are not data scientists but are fascinated by data and data science are curious about the skills required to pursue careers in data science.
The use of Big Data as a tool for generating insights has increased the demand for data scientists at the enterprise level across all industry verticals. Organizations are increasingly relying on data scientists to sustain, grow, and stay one step ahead of the competition, whether to refine the product development process, improve customer retention, or uncover new business opportunities.
Data Scientists must have the following skills:
The more advanced your position, as with most careers, the more skills you'll need to succeed. If you want to be a Data Scientist, you'll need to have certain skills regardless of your role.
Statistics and mathematics:
A good Data Scientist should have a strong background in math and statistics. Data Scientists in a data-driven business will be expected to understand multiple statistical approaches, such as maximum likelihood estimators, distributors, and statistical tests, in order to make recommendations and decisions. Understanding calculus and linear algebra is critical because they are linked to machine learning algorithms.
Modeling and analytics:
The ability of a Data Scientist to analyze and model data is dependent on their expertise in this area, so an excellent data scientist is expected to have a high level of proficiency in it. A Data Scientist should analyze data, run tests, and create models using critical thinking and communication skills to gain new insights and predict outcomes.
Methods of Machine Learning:
A high level of expertise is not always required, but some familiarity is expected. Machine learning, in addition to decision trees and logistic regression, enables other key skills that employers will be looking for.
To put theory into practice as a Data Scientist, you must have strong programming skills. You should be familiar with Python and R, as well as other programming languages. Object-oriented programming, basic syntax, functions, flow control statements, libraries, and documentation are all included under this umbrella.
Data visualization is an important part of being a Data Scientist because it allows you to communicate key messages and gain support for proposed solutions. To advance in their careers, Data Scientists must be adept at breaking down complex data into smaller, digestible chunks and utilizing a variety of visual aids (charts, graphs, etc.). See our post Creating Data Visualizations with Tableau to learn more about Tableau and why data visualization is so important.
Curiosity of the Mind:
The data scientist role is defined by a strong desire to solve problems and find solutions, particularly those that require thinking outside the box. A great Data Scientist is motivated by a desire to learn more about what data is telling them and how that knowledge can be applied on a larger scale.
Data cannot communicate unless it is manipulated, so an effective Data Scientist must have strong communication skills. Whether you are presenting your data to your team or to business leadership, communication can make or break the success of a project.
Data scientists will need business acumen to effectively use data and be valuable to their employers. Understand the company's key objectives and goals, as well as how they affect the work you do. Furthermore, you must develop solutions that meet those objectives while remaining cost-effective, simple to implement, and widely adopted.