Science and technology have advanced tremendously in the last decade. As a result, data science is deep-rooted in every aspect of our daily lives. From healthcare to digital marketing, mathematical tools derive crucial data from piles of data. So let us understand why data science is important.
This article will guide you and help you gain perspective on how a postgraduate program in data science can prove fruitful for your career. If you already have a strong data science foundation and programming skills, a post-graduation in data science will be a natural step forward.
The importance of data scientist jobs in the United States is growing annually. However, as more and more industries have started relying on data science, it is still considered one of the sexiest jobs of the 21st century.
According to the U.S. Bureau of Labor Statistics, employment of data scientists is projected to grow by 36% until 2031. So, post-graduation in data science is your answer to setting yourself apart from the rest of the crowd.
These numbers show that data science will be around for a while, and as the field grows, so will the number of available positions for qualified data scientists.
Key differences between Data Analyst Vs. Data Scientist
Data analysts use programming languages, software, and tools to collect, clean, and visually represent data to solve real-world business problems.
- Working together with top-level management to assess data requirements
- Using both primary and secondary resources to compile information
- Preparing data for analysis by cleaning and rearranging
- Applying statistical methods to large data sets to draw conclusions and make informed decisions
- Communicating results to facilitate data-driven decision making
It’s easy to need clarification on the roles of data analysts and data scientists since both seek to discover patterns and trends in data to help businesses improve their decision-making. However, data scientists are often more senior than data analysts and are tasked with various responsibilities.
Data scientists often face uncertainty when using more sophisticated data approaches to foresee potential outcomes. Their automated machine learning algorithms or predictive modeling procedures may process structured and unstructured data. This position is often seen as an upgrade from a data analyst’s. Some examples of typical daily activities include:
- Methods of data collection and Processing
- Creating ML and DL models for data mining in large datasets
- Building systems to track and evaluate data quality
- The development of data-viewing applications, dashboards, and reports
- Creating code to streamline the gathering and processing of data
Skills covered in a Data Scientist Degree
A post-graduate data scientist degree will cover the following skills:
- Natural Language Processing
- Exploratory data analysis
- Descriptive statistics
- Inferential statistics
- Model building and fine-tuning
- Ensemble learning
- Machine learning
- Deep learning
Reasons to pursue a Masters in Data Scientist
Let us explain what to expect from Ms. in the data scientist online course.
1. Advance your skills
Earning a master’s degree in data science will give you the knowledge and expertise to effectively gather, manage, analyze, and report on various data sources, formats, and trends. The advanced information and abilities you’ll gain during the Master of Science in Data Science program will equip you to make informed decisions about complex problems in the workplace.
2. Higher job prospects & salary
Gaining data science expertise may also pave the way to better-paying jobs at bigger corporations or relocation to the United States, where opportunities are booming for data scientists. Companies like Amazon, Deloitte, Target, banks, etc., are some of the companies hiring experienced data scientists.
According to Payscale, the average salary for a data scientist is $98,789 annually.
3. Build Relationships & Network
This is an ideal setting for a master’s degree program. You’ll join a carefully selected group of people who share your interests. You’ll make friends and connections worth keeping professionally as you participate in class and group initiatives. These colleagues will provide some assistance in resolving an issue.
4. Learning from peers
The online curriculum designed will help you learn from experts and peers, which is a great way to learn. In the online session, faculty and alums will discuss pressing issues in the business world and offer practical advice you can use immediately.
Career opportunities for a Data Scientist Degree
After pursuing a master’s degree in data science, professionals can move on to bigger and better roles in the following areas:
To help businesses make sense of quantitative business data and better guide their choices, statisticians collect, analyze, and interpret numerical data to reveal trends and patterns. They use mathematical approaches, statistical methods, and computational tools to make sense of complex data and produce reliable business forecasts.
2. Big Data Engineer
The role of a Big Data Engineer is to assess a business’s software and hardware requirements. They are the go-to professionals overseeing an enterprise’s data infrastructure and architecture. They create, test, deploy, and keep up Big Data systems using technology like MongoDB, Spark, etc.
3. Data Architects
Data architects should have solid foundations in calculus, statistics, and related fields. Expert in relational database management systems (RDMS), database design, and cloud computing. So, if you wonder, do data scientists code? After completing the post-graduation degree, they must be proficient in coding.
4. Full-Stack Developers
According to a student’s perspective, earning a Master of Science in Data Science will equip you with cutting-edge knowledge and practical experience in the business. Upgrade your knowledge and get a worldwide perspective by enrolling in a master’s degree program at Simplilearn. Check out Simplilearn’s master’s degree program, where you can earn your degree at your own pace and study with industry leaders.
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