Why You Should Consider A Career In Data Science

Why You Should Consider A Career In Data Science- The demand for data scientist globally is on the rise daily. It is one emerging and fast-growing field in the technology world. In this article, , we would consider why this huge rush/surge in data science and why you should consider a career in data science.

Why You Should Consider A Career In Data Science

1. Data Scientists are well paid

Persons with career in data science are well-paid globally. The more experience you have in the career, the greater your remuneration. Data scientists working with USA companies are the most paid while least paid data scientists are the ones working with African and Asian companies. So if you desire a career that would really pay you well, then you should go for a career in data science.

2. Data scientists are in high demand globally

The field of data science is a fast growing one globally. In the last few years, the demand for data science has really shot up while the supply is still short. Unlike, some emerging technologies that fizzle out after sometime, data science has not, but rather keep growing daily.  Data science has brought so great value to businesses, even Science and technology. Data science is not a field that will fizzle out not now or in the nearest future. So if you desire a career for the future, then you pick a career in data science.

3. Data Science is an interesting field

If you desire a career with lots of interesting features, then you should pick up a career in data science. It is one field that helps you see things from a different perspective. You can take a peep into the future and take some decisions to avert any occurrence or propel something to happen. It is one field that helps people to make future predictions.

4. It is a career that boosts creativity

As a Data Scientist, you will have to be dealing with complex issues, simplifying them into what others can understand. A number of times, tackling complex problems requires some creativity . So if you desire a career that boosts creativity, you should go for a career in data science.

5. Data Science is a diverse field

Data science is one career that enhances or is open to open of different background. It is quite easy for an individual from any other field to cross over into data science. You don’t need any degree in Computer science or Engineering to begin a career in data science. The most beautiful thing is that you can even combine the field of data science with your current profession.

6. Data Science is a prestigious career

A career in data science is a very prestigious one. People in such role are held in high esteem and seen as people whose decisions are critical to the continual existence of a company. However, to attain such a critical position, you need a lot of expertise and experience.

7. A Career that gives you lot of work options

As a data scientist, you can work anywhere. Most companies require the role of a data scientist . Data scientists are needed by the company in making future predictions and plans. You can never be out of job as a data scientist.

It is one of the careers of the future that would be relevant in the future is a career in data science. It is a field that is daily evolving and is relevant in a lot of industries. Some of the fields that have emerged already includes Artificial intelligence (AI), Machine Learning (ML), big data. More will still emerge.

8. It is a remote-friendly job

With a career in data science, you can work remotely. You don’t have to go through the street of waking up daily and commute to work. You can get to work and get results right in your balcony, garden, etc.

How To Begin A Career In Data Science

• Get a bachelor degree in Data science , Data analytics , Computer Science , Engineering , Mathematics and related field.
• Go for internship, work on projects to get some experience
• Go for higher degrees e.g Master’s in data Science
• Take short courses/ certifications
• Volunteer
• Update your resume/ go get a job

What Job Can I do With A Career In Data Science

• Data Scientist
• Data Engineer
• Data Analyst
• Data Architect
• Machine/learning engineer
• Business analyst

1. Data Scientist

They are data experts , working closely with business leaders to understand an organization’s objectives and map out  data-driven strategies-driven strategies to accomplish such objectives. Their role include gathering a large quantity of data, analyzing it , separating critical information and using tools like Python, SAS , R programming to get some insights that can be used to boost efficiency and productivity of an organization.

Roles Of A Data Scientist

• Gather and analyze data
• Generate solutions to business problems using data gathered
• Data presentation using different data visualization techniques and tools
• Work with team members to create data strategy

2. Data Analyst

Data Analysis involves collection, , sorting and interpretation of sets of data to solve a particular problem. Data analysis is in 5 phases:

• Identification of data to be analysed
• Collection of data
• Cleaning of data
• Analysis of data
• Interpretation of data

Roles Of A Data Analyst

i. Gather Data

They gather data by carrying out surveys, buying data sheets, etc.

ii. Clean up data

Data gathered are raw with some irrelevant, duplicate and wrong infos. Data analyst separate the useful datas from the ones that are not.

iii. Model data

They design structures of a database, categorise data , etc.

iv. Interpret data

They interpret data to find trends, patterns, etc.

v. Present the data

This is usually done in the form of charts, , graphs, reports, etc.

Some tools used by data analyst including SQL, Python, Microsoft excel , Tableau, SAS, Microsoft power PI, Dupyter notebooks.

3. Data Architects

They are IT professionals who employ their computer science and design skills to analyze and review the data infrastructure of a business. They also plan future databases and implement solution to store up and manage data for businesses and their users . Data Architects can work in virtually most industries ranging from health, finance , entertainment, etc.

Roles of Data Architects

• Analyze, plan and define data architecture
• Create and implement data management processes and techniques
• Develop application programming interfaces (APIs) to retrieve data
• Research data acquisition opportunities
• Create techniques to ensure data accessibility and accuracy

4. Data Engineer

Data engineers are involved in the design and building of systems that will aid / enhance collection, storage and analysis of data. They make data accessible usable by organizations .

Roles Of A Data Engineer

• They acquire data sets relevant to the need of a company
• Develop algorithms that will translate data into useful information
• Build, test, run and manage database pipeline architectures.
• Create new data validation techniques

5. Machine Learning Engineer

This is an IT personnel who focus on research, builds and design self-artificial intelligence (AI) systems. They create and design AI algorithm that is capable of learning and making predictions. They usually work as part of a team (data science team) such as data scientist, data analyst, data engineers, etc.

Role Of A Machine Learning Engineer

• They design machine learning systems
• Verify data quality
• Perform statistical analysis
• Research and implement ML algorithms and tools
• Run machine learning tests

Last Word

A career in data science is one of the jobs of tomorrow. Out of data science has emerged big data, machine learning , artificial intelligence and many more to come. So if you are out there in search of a career that will give you a secured future, then choose a data science.

Frequently Asked Questions

Reference

• www. towardsdatascience. com – Why should you consider a career in data science
• www. onlinegrad.syracuse. edu- How to start a career in Data Science
• www. coursera. org – Your guide to Data science careers( How to get started)
• www. emeritus. org – What are the roles and responsibilities of a Data Scientist
• www. techtarget. com -Machine Learning Engineer

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