What is Data Science?
How lucrative is Data Science?
Do I need to be a Maths guru to become a Data Scientist?
What can I do with a Data Science Degree?
Below are the answers to your most pressing questions about Data Science.
Data Science is the science of sourcing, storing, managing, and analyzing data for effective decision-making. A Data Scientist helps businesses and corporations curate data to achieve policy goals, drive organizational improvement, and enhance profitability.
In the past six years, Data Science has topped the list of the best jobs in the US four times in a row. And in the last two years which it hasn’t been top, it is second. This explains the high demand for Data Scientists across the globe. According to Indeed, there are about 293 Data Science job openings in Nigeria (November 2021).
Without mincing words, Mathematics and Statistics are required for an advanced degree in Data Science. However, the good news is that, for most data science positions, the only kind of math you need to become intimately familiar with is the need to understand the fundamental concepts of descriptive statistics and probability theory.
As you can see, Data Science is an interesting and versatile specialization. But what are the career paths available once you have completed your Data Science degree?
Here are 8 of them:
Data analysis is typically the entry-level position in the data science field. A data analyst looks at a specific industry or company data and uses it to solve a business question(s). Data Analysts’ decisions are usually conveyed to management or other departments within the organization. Analyzing a Facebook ad campaign is an example of Data analysis.
A Data Scientist collects, analyzes, and interprets a large amount of data. They process complex information, study data patterns, and engage in prediction modeling to make strategic decisions.
Machine Learning Engineer
A Machine Learning Engineer is a Data Science professional who creates programs and algorithms. These programs and algorithms then aggregate data, learn from them, and form predictive patterns without human intervention. Machine Learning enables machines and computers to make decisions (such as self-driving cars) and improve user experience (such as social media feeds).
The role of an applications architect is to track applications used within a business and how they interact with each other and with users. They can also build application infrastructure such as User Interface.
Machine Learning Scientist:
A Machine Learning Scientist works in the research and development of new data approaches and algorithms that are used in adaptive systems and deep learning such as AI. They build methods for predicting suggestions or recommendations for products and services.
Data Architecture involves solutions that are built for performance and design analytics applications for multiple platforms. Data Architects create new database systems and improve the performance and functionality of existing ones. They also manage the access of other professionals such as database administrators and analysts.
Data Engineers build and manage the systems that collect, organize, and convert raw data into usable information for Data Scientists. They process stored data and maintain the data ecosystem within an organization.
Business Analysts serve as the bridge between the business and technology departments of an organization. They work with Data Scientists and Architects to steer new business processes with technological solutions. Automating the inventory restocking process is an example of a business analyst’s role.
Become a Data Science Professional Today!
With many organizations adopting tech-based solutions, the demand for Data Science professionals is on the rise. And roles come with mouthwatering remuneration that sets you firmly on the path of success.
If you are looking to start a Data Science career, the Ustacky Data Science Microdegree upskills you with mastery in Data Science fundamentals and prepares you for expert proficiency.