Is a Data Science Career Transition Worth Pursuing? The Beginner Guide

Moneymagpie Team 29th Feb 2024 No Comments

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Data science is one of those careers grabbing a lot of attention because it holds the power to transform businesses. The combination of coding and statistics allows data scientists to transform data, enabling businesses to witness more ROI (Return on Investments) and analyze their social impact. Due to its popularity, many are planning data science career change. However, the career transition to data science is tricky.

Data Science- The Role and the Skills
Job roles that come with the Data Science field
Career transition to data science- Frequently Asked Questions

Data Science- The Role and the Skills

Data science is the brainchild of the combination of data mining and statistics. On top of that, it leverages the power of software development, research, and machine learning to transform raw data into refined data, allowing users to conduct businesses more efficiently.

Data science is here because technology is evolving, and there is a need to access the data to make sense. Data science is essential to society’s functions, such as tracking, restocking, analyzing campaigns, and managing medical records.

Before planning the career switch to data science, it is important to understand the technical skills required to thrive in this field. The skills are

Machine Learning (ML)
Deep Learning
Understanding of statistical data
Coding
Mathematics
Data visualization
Experience with Hadoop, SAS, Python, and other tools
Statistics

The data science career transition requires technical skills. This field also involves collaborating with engineers, coders, analysts, developers, and business managers. For that, you will also need soft skills like:

Communication skills
Curiosity
Storytelling
Teamwork
Problem-solving skills
Logic building
Critical thinking

Job roles that come with the Data Science field

Data science is a vast field, with many companies offering different job roles. If you are changing career to data science, it is important to have insights about different types of job roles out there.

Data scientist

Data scientists are an integral part of a team that designs models using programming languages using Python. After that, they transform the data into applications. Often working as a whole, these scientists collaborate with entities such as business analysts to predict the future.

A data scientist’s average salary is $102,800.

Skills required: ML and deep learning, statistics, mathematics, programming languages, data mining, SQL, Hadoop.

Data analysts

Unlike data scientists, analysts leverage the power of structured data to solve business issues. The data analysts use tools such as SQL, Python, and R to clean and acquire data and make it recognizable. The data is then used to predict trends and make informed decisions.

A data analyst’s average salary is $64,798.

Skills required: Programming languages, data visualization, mathematics/statistics.

Data Architect

The architect plans and designs the blueprints of data management systems. They ensure that data is placed accordingly and maintain all types of data. Moreover, they also oversee the underlying infrastructure. Their main goal is to provide employees with refined data without any hurdles.

A data architect’s average salary is $122,700.

Skills required: Programming languages such as Python, Data mining, management, and machine learning.

Data Engineer

Another popular field in data science is data engineering. These engineers manage and prepare large amounts of data, optimize pipelining processes, and prepare data for analysts to analyze. The engineers make data accessible so businesses can improve their performance.

A data engineer’s average salary is $95,000.

Skills required: Understanding of NoSQL databases, Hadoop/apache, and Java.

Career transition to data science- Frequently Asked Questions

Yes, there are many options available with data science. So, the question is how to make the data science career switch. Well, here is an FAQ section to help you.

What educational background do I need?

The best method to get started in the data science field is to get a bachelor’s degree (Computer science, IT, Data Science, Software engineering).

Do I need additional certifications for entry into the data science field?

We will just say, “The More, The Merrier.” Any online course or certification can help you land jobs in this field. You can enlist these courses on your LinkedIn profile to attract potential employers.

What type of experience do I need to get the job?

After getting the professional degree and online certification, you need some experience. The best option is getting an internship or an entry-level job to get started in this field.

Final Verdict

Entry into data science is getting harder daily since there is a lot of competition nowadays. However, that doesn’t mean a career transition to data science is impossible. With the right steps and proper information, it can lead you towards places that will be a game changer for your career.

Author: Gregory Swenson

Gregory is an experienced IT professional with a knack for solving complex tech challenges. With over a decade in software development and technology consulting, he shares his insights and expertise through articles to help others navigate the IT landscape.

Disclaimer: MoneyMagpie is not a licensed financial advisor and therefore information found here including opinions, commentary, suggestions or strategies are for informational, entertainment or educational purposes only. This should not be considered as financial advice. Anyone thinking of investing should conduct their own due diligence.

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