Entering the World of Data Science: Preparation and Required Skills
What is Data Science?
Data science is a combination of fields such as math, statistics, and programming, combined with advanced analytics, artificial intelligence, and machine learning. The goal of data science is to use data from a company to find useful information that can help improve the company’s performance.
The data science process involves several steps. First, data is collected from various sources, such as websites or real-time data streams. This data can be in different formats. Once the data is collected, it is stored and cleaned to ensure it is ready for analysis.
In the next step, the data is analyzed to find patterns and trends. This is similar to detective work, where you look for clues to help solve a secret. The results of this analysis are then used to make predictions and models.
Finally, the results are presented in a way that is easy to understand. This can be done through reports or visualizations, using languages like R or Python. The goal is to make the results clear and easy to understand for people who don’t have a background in data science. This helps decision-makers within the company make informed decisions that are based on data insights.
What are the career prospects for a data scientist?
The career outlook for data scientists looks quite bright, especially since many businesses are starting to use data to make important decisions. In the last ten years, the amount of data available has grown significantly, and we have seen a huge increase in the need for people who can use this data. This makes data science a very useful tool in many fields.
One of the best things about being a data scientist is that the risk of this job being replaced is not great. The demand for data scientists is growing fast, with an average increase of 50% every year. But, most of the complex analysis performed by data scientists is still done by humans.
What skills are needed?
To enter the data science industry, there are several technical and non-technical skills that need to be mastered. First, programming skills are very important in the work of a data scientist. Programming languages that are often used are Python and R.
Furthermore, data scientists must have a strong understanding of statistics and math. This is essential for conducting effective data analysis. This ability allows a data scientist to interpret data and create accurate statistical models.
Another important skill is mastery of machine learning. The ability to apply machine learning algorithms is essential in the work of a data scientist. Some of the approaches that can be used are unsupervised learning and supervised learning, which help in making predictions from data.
A data scientist must also understand databases and how to access data from them. Some of the tools commonly used for databases are SQL Server, MySQL, Oracle, and NoSQL. This understanding is important to ensure that the data used in the analysis is valid and relevant.
Furthermore, the ability to communicate the results of data analysis to other teams within the company is very important. Data Scientists must be able to explain the results of their analysis clearly and effectively. This is important to ensure that the results of the analysis can be understood and used by other parties within the company.
Critical thinking and rigor are also important requirements in the job of a data scientist. The ability to apply the right methods in data processing and achieve the objectives of the analysis is key in this job.
Finally, a data scientist must understand the company’s business model and requirements in order to provide the right analysis and recommendations. This understanding allows the data scientist to provide appropriate and effective solutions for the company.
Prepare for the interview
1. Review your resume and cover letter: You will probably be asked about the things written there. This will help predict the questions that will come up.
2. Preparation for questions: An interview is a dialog where you can ask about anything if you have questions. It also shows initiative if you have relevant and insightful questions to ask.
3. Preparation of salary expectations: Know what salary to ask for based on the job title and skills.
4. Preparation of answers to common questions: This could include why you want to work there, what to expect from managers, and whether you prefer to work independently or in close contact with a team.
5. Conduct a mock interview with a friend: This can help you spot issues you haven’t thought of.
6. Get enough rest: Make sure you sleep well and are not tired as this will hurt your chances of getting hired.
Different types of interviews require different preparation:
1. Phone interview: Ensure a good and stable connection, find a quiet place.
2. Video call: Have a stable and fast internet connection, install the necessary software for video calls, and pay attention to the environment.
3. Face-to-face: Know how to get to the interview location, practice your body movements, and don’t arrive late but also don’t arrive too early.
To prepare yourself for your career, COMPFEST Talks at COMPFEST Main Event can be an interesting event to attend. COMPFEST brings prominent speakers who are ready to provide valuable insights and knowledge to prepare yourself to enter the world of work. Through COMPFEST Talks, you will get the opportunity to learn directly from experts in various fields and know more about the latest developments in the world of technology and industry. So, don’t miss this opportunity and register now! Be sure to follow us on social media: Twitter, Instagram, Facebook, and LinkedIn to not miss the latest updates from COMPFEST. (Editorial Marketing/Iqbal)
Reference:
- https://www.ibm.com/topics/data-science
- https://365datascience.com/career-advice/data-scientist-job-outlook/
- https://www.datacamp.com/blog/data-science-interview-preparation
- https://www.computerscience.org/careers/data-science/how-to-become/
- https://dqlab.id/skill-data-scientist-yang-dibutuhkan-dunia-industri-pemula-wajib-tahu
- https://www.techtarget.com/searchenterpriseai/feature/The-future-of-data-science-jobs
- https://online.hbs.edu/blog/post/data-science-skills-for-beginners
