How to become a data scientist
Data science is a field of study that combines statistics, maths, and domain expertise to extract quality insights from data. It is about using data to create as much impact as possible for organizations. The impact can be in multiple forms such as insights, data products, or in the form of product recommendations for a company.
What do data scientists do?
The basic approach towards solving organizational problems by data scientists is:
👉Looking at the problem and enquiring for related issues connected.
👉Explaining the issue and understanding its impact
👉Predicting the expected outcomes and determining which outcome is likely to be positive
👉Analyzing the methods to solve these problems with technological solutions.
These professionals possess the ability to understand the data structure, analyze data and write concise codes, and create graphs and charts to present the results. They crack highly complex data problems with their strong expertise in certain scientific disciplines. They work across a variety of data science topics such as:
◾ Predictive analysis
◾ Social media analysis
◾ Business intelligence
◾ Natural language processing
◾ Web analytics
The most basic job role performed by data scientists is identifying data and using software to evaluate the identified data. Their job roles can range from software engineers to having to write machine learning algorithms.
What are the academic qualifications required?
◾ Get a bachelor’s degree in computer science, business, math, statistics, physical science, or any other computer-related or data science field.
◾ Gain experience in the field one intends to work in. For example: — business, healthcare, manufacturing, education, and banking are the top industries that use data science.
◾ Learn the vital skills required to perform the job role,
◾ Earn data scientist certifications to substantiate and uphold learned skills.
What technical skills do data scientists need?
Linear algebra and statistics: Data science requires an individual to learn linear algebra and statistics first before heading towards more advanced materials and machine learning algorithms. This is because statistics are extremely important to interpret proper results, as it is crucial to find clusters while evaluating data in additional structures or data which is dependent on time, space, and other variable factors.
Python coding: Data scientists often need to prototype solutions to a given problem quickly to further start iterating and arriving at better solutions. This part needs to be done quickly to put solutions into working code easily with a simple syntax. Slowing down this process will disrupt the entire progress of problem-solving. It is recommended for individuals to opt for data scientist certification online that offers expertise in Python skills, which can help in better competitiveness and skill polishing.
What are the non-technical skills are required to work on?
◾ Critical thinking and problem solving both in terms of making specific decisions to solve a problem and understanding the big picture to make certain decisions.
◾ Good project management and communication skills with the ability to understand data.
◾ Understanding the significance of privacy issues and data integrity and users.
What are the certifications available for data scientists?
Capabilities of data scientist is one of the most challenging jobs to do in the business world. Data scientist certifications are specifically designed to provide professionals with a winning edge to perform tasks and to learn various complex skills to be applied while solving problems with machine learning. A basic requirement to apply for these certifications is a bachelor’s degree with a minimum of five years’ experience in the related field. However, this may vary depending on the certification type one chooses to earn. Here are the best data scientist certifications by various institutions that offer updated skill sets, which are hard to find in the desired industry otherwise.
◾ Certified Data Science Developer Certification (CDSD) by International Association of Business Analytics Certification (IABAC)
◾ Senior Data Scientist (SDS) by Data Science Council of America (DASCA)
◾ Data Science Professional Certification (DSP) by IBM
◾ Advanced Analytics Professional Program by SAS Academy
Data science professionals seeking to pursue a job role as a data scientist can earn any one or multiple certifications, completing the curricula to reach goals in a structured approach.
This was all about the skills and certifications required to become a data scientist. This field will not subside anytime sooner. Hence, it is the right time for graduates and working professionals to build a career in data science.