Data science is a versatile field and a career in this field is about data, decision-making, statistics, and calculations. It involves different tasks related to working with data by using different features and tools to take the company to new heights. It is a new area and most of the students wonder about the ways they can pursue a career in this field. Here is a detailed guide to building a data science career, which you can use to understand the concept of data science and job roles performed by data science professionals. Depending on your interests and education, you can choose a job role in this field.
What is data science?
Data science is a field of study that binds knowledge of statistics, programming skills, and domain expertise to extract meaningful information. It is about extracting, evaluating, managing, storing, and visualizing data to generate insights. These insights help organizations to make data-driven decisions. This field uses unstructured and structured data that has its roots in computer science, math, and statistics. Currently, as per an IBM report, there is an abundance of various positions in this field at 14.3 percent with a lucrative pay scale and is a highly in-demand career.
How to build a career in data science
Let’s explore the qualifications, salaries, skills, and job roles required for professionals seeking a data science career.
If you are someone who likes to work with numbers and is familiar with basic concepts of statistics and math, you can become a data science professional. Here are a few tips that can help you start a career in this field:
- You need to have a bachelor’s degree in statistics, computer science, math, engineering, technology, and related fields
- You can pursue internships with any data science company
- Take up online data science courses and earn relevant certifications
- Be aware of the basics of computer vision, speech processing, natural language processing, and bioinformatics, and other important aspects
- You can also opt for an MBA in data science.
One can get paid handsomely in data science as it is a highly in-demand field these days while the supply is comparatively low. According to Glassdoor, the average salary of a data scientist at McKinsey ranges from USD 90,000 to 1,20,000 per year.
Data science skills
There are certain data science skills one must be proficient in to work in this field:
You will require strong programming skills as a data scientist or an analyst as most of the organizations will expect you to be well-worse in R and Python as well as other programming languages. Basic functions and syntax, object-oriented programming, libraries, and flow control statements all of these data science skills fall under this umbrella.
Machine learning methods
While being an expert in this area is not specifically required, but it is always preferred to have a familiarity with logistic regression, decision trees, and other elements enabled by machine learning. Potential recruiters will be looking for such skills.
Math and statistics
Any data-driven business will expect you to understand different approaches to statistics including statistical tests and distributors to make decisions and provide recommendations. Linear algebra and calculus are vital as they’re both tied to machine learning algorithms.
What are the Job roles in data science
The data science domain offers a wide range of opportunities for professionals and students. The following is a list of a few key roles you can choose in your data science career.
A data scientist is responsible for gathering, evaluating, and interpreting extremely large amounts of data, and helping companies make better decisions.
A data engineer is an IT professional whose key job is to prepare data for operational and analytical uses. They aim to make data accessible easily and to maximize their company’s big data ecosystem.
A data analyst serves as a gatekeeper for a company’s data so stakeholders can use it to make strategic business decisions. It is a technical role that requires proficiency in computer modeling, math, and analytics.
Data architects are senior visionaries who translate the requirements of business into technical requirements and define data principles and standards. They coordinate and collaborate with stakeholders, partners, multiple departments, and external vendors.
As discussed, data science is a lucrative field that is ever-evolving. The above details will help you make a wise decision on whether or not to take this up as your career in the future.