- Data Science Tutorial
- Data Science - Home
- Data Science - Getting Started
- Data Science - What is Data?
- Data science - Lifecycle
- Data Science - Prerequisites
- Data Science - Applications
- Data Science - Machine Learning
- Data Science - Data Analysis
- Data Science - Tools in Demand
- Data Science - Careers
- Data Science - Scientists
- Data Scientist - Salary
- Data Science - Resources
- Data Science - Interview Questions
- Data Science Useful Resources
- Data Science - Quick Guide
- Data Science - Useful Resources
- Data Science - Discussion
Data Science - Careers
There are several jobs available that are linked to or overlap with the field of data scientist.
List of jobs related to data science −
Below is a list of jobs that are related to data scientists.
Data Analyst
Data Scientist
Database Administrator
Big Data Engineer
Data Mining Engineer
Machine Learning Engineer
Data Architect
Hadoop Engineer
Data Warehouse Architect
Data Analyst
A data analyst analyses data sets to identify solutions to customer-related issues. This information is also communicated to management and other stakeholders by a data analyst. These people work in a variety of fields, including business, banking, criminal justice, science, medical, and government.
A data analyst is someone who has the expertise and abilities to transform raw data into information and insight that can be utilized to make business choices.
Data Scientist
A Data Scientist is a professional who uses analytical, statistical, and programming abilities to acquire enormous volumes of data. It is their obligation to utilize data to create solutions that are personalized to the organization's specific demands.
Companies are increasingly relying on data in their day-to-day operations. A data scientist examines raw data and pulls meaningful meaning from it. They then utilize this data to identify trends and provide solutions that a business needs to grow and compete.
Database Administrator
Database administrators are responsible for managing and maintaining business databases. Database administrators are responsible for enforcing a data management policy and ensuring that corporate databases are operational and backed up in the case of memory loss.
Database administrators (sometimes known as database managers) administer business databases to ensure that information is maintained safely and is only accessible to authorized individuals. Database administrators must also guarantee that these persons have access to the information they need at the times they want it and in the format they require.
Big Data Engineer
Big data engineers create, test, and maintain solutions for a company that use Big Data. Their job is to gather a lot of data from many different sources and make sure that people who use the data later can get to it quickly and easily. Big data engineers basically make sure that the company's data pipelines are scalable, secure, and able to serve more than one user.
The amount of data made and used today seems to be endless. The question is how this information will be saved, analyzed, and shown. A big data engineer works on the methods and techniques to deal with these problems.
Data Mining Engineer
Data mining is the process of sorting through information to find answers that a business can use to improve its systems and operations. Data isn't very useful if it isn't manipulated and shown in the right way.
A data mining engineer sets up and runs the systems that are used to store and analyze data. Overarching tasks include setting up data warehouses, organizing data so it's easy to find, and installing conduits for data to flow through. A data mining engineer needs to know where the data comes from, how it will be used, and who will use it. ETL, which stands for "extract, transform, and load," is the key acronym for a data mining engineer.
Machine Learning Engineer
A machine learning (ML) developer knows how to train models with data. The models are then used to automate things like putting images into groups, recognising speech, and predicting the market.
Different roles can be given to machine learning. There is often some overlap between the jobs of a data scientist and an AI (artificial intelligence) engineer, and sometimes the two jobs are even confused with each other. Machine learning is a subfield of AI that focuses on looking at data to find connections between what was put in and what was wanted to come out.
A machine learning developer makes sure that each problem has a solution that fits it perfectly. Only by carefully processing the data and choosing the best algorithm for the situation can you get the best results.
Data Architect
Data architects build and manage a company's database by finding the best ways to set it up and structure it. They work with database managers and analysts to make sure that company data is easy to get to. Tasks include making database solutions, figuring out what needs to be done, and making design reports.
A data architect is an expert who comes up with the organization's data strategy, which includes standards for data quality, how data moves around the organisation, and how data is kept safe. The way this professional in data management sees things is what turns business needs into technical needs.
As the key link between business and technology, data architects are becoming more and more in demand.
Hadoop Engineer
Hadoop Developers are in charge of making and coding Hadoop applications. Hadoop is an open-source framework for managing and storing applications that work with large amounts of data and run on cluster systems. Basically, a Hadoop developer makes apps that help a company manage and keep track of its big data.
A Hadoop Developer is the person in charge of writing the code for Hadoop applications. This job is like being a Software Developer. The jobs are pretty similar, but the first one is in the Big Data domain. Let's look at some of the things a Hadoop Developer has to do to get a better idea of what this job is about.
Data Warehouse Architect
Data warehouse architects are responsible coming up with solutions for data warehouses and working with standard data warehouse technologies to come up with plans that will help a business or organization the most. When designing a specific architecture, data warehouse architects usually take into account the goals of the employer or the needs of the client. This architecture can then be maintained by the staff and used to achieve the goals.
So, just like a regular architect designs a building or a naval architect designs a ship, data warehouse architects design and help launch data warehouses, customizing them to meet the needs of the client.
Data Science Job Trends 2022
By 2022, there will be a big rise in the need for data scientists. IBM says that between 364,000 and 2,720,000 new jobs will be created in the year 2020. This demand will continue to rise, and soon there will be a 700,000 openings.
Glassdoor says that the top job on its site is for a Data Scientist. In the future, nothing will change about this position. It is also looked at that the job openings in data science are open for 45 days. This is five days longer than the average job market.
IBM will work with schools and businesses to create a work-study environment for aspiring data scientists. This will help close the skills gap.
The need for data scientists is growing at a rate that is a power of two. This is because new jobs and industries have been created. This is made worse by the growing amount of data and the different kinds of data.
In the future, there will only be more roles for data scientists and more of them. Data scientist jobs include data engineer, data science manager, and big data architect. Also, the financial and insurance sectors are becoming some of the biggest employers of data scientists.
As the number of institutes that train data scientists grows, it is likely that more and more people will know how to use data.