When it comes to selecting a career option, it creates lots of confusion. Our mind hits with this vs that confusion. Data scientist and full stack developer career options are wonderful opportunities. But which one you should select?
In this article, we will talk about all aspects of Data scientist and full-stack developer career options. So, you get the clarity associated with data scientist vs full stack developer.
Data Scientist: An Overview of the Occupation
In this modern era, data is key to success. No matter what field it is. There is data and you require these data to analyze, examine, and learn whether you’re going towards the right path or not.
Finance, marketing, government policies, health care, and all other sectors need to deal with data to get important information.
Data science is the process of extracting meaningful data from unstructured databases. Data science professionals, called data scientists, are required to use multiple techniques that help in cleaning, processing, and analyzing data to find the pattern and insights in it.
The data scientist is one of the most sought-after professions that allows you to get high-paying, reputed jobs in multiple companies and franchises.
Data Scientist Core Responsibilities
The core responsibilities of a data scientist are:
- Predicting the future behavior of customers and users after analyzing the data.
- Communicating their findings effectively to non-technical people.
- Collect, analyze, and present data accurately before stakeholders.
- Identify trends, pain points, and other factors that can benefit business.
- Present solutions and strategies to tackle business challenges.
- Use machine learning tools for data management, data analysis, and data extraction.
Skills Required for Data Scientist
The data science profession requires certain skills which include:
1. Programming language
Data science process requires the use of a programming language to organise unstructured data sets. Hence, to excel in this field, you need to have knowledge of various programming languages, especially Python & R.
2. Statistics & Probability
Data scientists require the knowledge of statistics and probability to write high-quality data for machine learning models and algorithms. The major statistical techniques you need to acquire are probability distributions, over and undersampling, bayesian and frequentist statistics, and dimension reduction.
3. Database Management
Database management is a crucial skill as it requires you to extract, analyze, and present useful information. Moreover, you need to collect data from various sources and arrange them in an orderly manner.
4. Machine Learning
Machine learning is a subset of artificial intelligence which is crucial for data scientists. It helps them gather and synthesize data more efficiently and also helps them in predicting the outcomes of future data sets.
5. Cloud Computing
Cloud computing is a place where you can store and visualize your data. As, a data scientist you must know cloud computing skills, so you can effectively access cloud-based databases and frameworks
6. Problem Solving
Problem-solving is a non-technical skill but crucial for data science professionals. As a data scientist, you require the ability to find solutions for business problems and challenges. Moreover, you must have analytical thinking and decision-making skills.
7. Communication Skill
Since, as a data scientist, you require to communicate your ideas, data outcomes, and other significant information to your team, and reporting person. Hence, you require good communication skills.
Full Stack Developer: An Overview of the Occupation
Full stack development is another most sought-after profession in the IT field. A full-stack developer is someone who develops a complete website including the front end, back end, and database.
The full stack developer is highly demanded in the field because of its specialty of bridging the gap between, frontend and backend, providing a better understanding to web or application development.
From MNCs to small startups all require a full-stack developer professional to manage website and application development.
Full Stack Developer Core Responsibilities
- Developing front-end website architecture
- Creating servers and databases
- Working in collaboration with web designers
- Testing and debugging software
- Developing Full-cycle application
Skills required for Full Stack Developer
Full Stack Developer profession requires certain skills which include:
1. Front-end Technologies
Full-stack developers are required to do client-side development. So, they must have expertise with front-end development languages such as Javascript, HTML, CSS, etc.
2. Backend Technologies
Backend development is an essential part of Full-stack development. To do so, you need command over some programming languages such as Java, and Python. Moreover, you also need to know some frameworks like NodeJS, ExpressJS, Django, and Flask.
3. Database Management
As, a full-stack developer, you might be required to manage databases. So, you must have the ability to manage large databases.
4. Creativity
A full-stack developer generally works as a leader for the development team. Their creativity skills help the team in designing a website that is user-friendly and aesthetically pleasing.
5. Problem-solving skills
Like data scientists, full-stack developers also need problem-solving skills. It’s crucial for them to predict errors and develop a bug-free application.
6. Understanding of Version Control Systems
Full-stack developers need to understand the version control system as they are required to manage the project, track its entire history, and more. As a full-stack developer, you will need to learn various version control systems like GIT, GitHub, Apache Subversion, and GitLab.
7. Time Management Skills
Time management skill is an essential skill for any professional. The time management skills let you meet your deadlines while ensuring that you properly execute your tasks.
Now, that you know the required skills and responsibilities for both professions, you might think about which you should select.
Also Read: Why python is most suitable for Deep Learning, Machine Learning, and Artificial Intelligence
Factors to Consider for Data Scientist vs Full Stack Developer Career
| Essential Factors | Data Scientist | Full Stack Developer |
| Salary for Fresher | ₹3.9 LPA | ₹3.6 LPA |
| Salary Mid-level Professional | ₹9.9 LPA | ₹5.4 LPA |
| Salary for Experienced | ₹13.3 LPA | ₹9.0 LPA |
| Number of professionals | Around 23 million | Around 2 Lakhs |
| Demand | Increasing 35% each year | Increasing 12% each year |
The Bottom Line
Both full-stack developer and data scientist are good career options, you can choose any. However, you must know to excel in any field, you’ll be required to learn the skills and understand its responsibilities.
To learn data science or full stack development, you can enroll in its respective courses and take your first step.
You must know some IT training institutes offer full stack development and data science courses with 100% placement guarantees.
Vikas Maurya is a professional blogger and Data analyst who writes about a variety of topics related to his niche, including data analysis and digital marketing.
