Data Science Alternative Career Path -NBD Lite #13
Career choices you might want to think of...
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Data science is still the job of the year, especially with all the hype in generative AI.
However, it’s common that the demand for data science jobs is way lower than that of applicants.
Also, many employers still prefer senior data scientists over juniors.
That’s why many students learning data science find it hard to find a job.
However, it doesn’t mean what you learn will go to waste.
There are still many alternative career paths for those who know data science.
For both beginners and professionals, there are various jobs where you can implement your data science skill set.
So, what are these alternative career paths? Here are summary alternatives you can think of.
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1. Data Analyst
The first career choice you should consider is the data analyst.
Data analysts usually work with the raw data to answer the business's specific questions.
Data analysts often work in each department to provide detailed ad-hoc analysis for the specific project and perform statistical analysis to gain insight from the data.
They can use SQL, programming languages (Python/R), and data visualization tools, which are skills that data science has learned. Â
If this is an alternative career path, you could attend a Free Data Analyst boot camp for Beginners, as Bala Priya C explains.
2. Data Engineer
Data engineering has become an important position to provide a stable and high-quality data stream.
A data engineer would be responsible for many data scientist jobs in the company.
Data Engineers focus on the backend infrastructure to support data tasks and maintain the architecture for data management and storage.
They also build data pipelines as per requirements, including collection, transformation, and delivery.
They must be adept in additional skills, including SQL, database management, and big data technologies.
To learn more about the Data Engineer career, read the article Free Data Engineering Course for Beginners by Bala Priya C.
3. Machine Learning Engineer
People sometimes mistake data science and machine learning engineering for the same job, but they are different.Â
Machine Learning engineers focus more on the technical aspects of machine learning deployment into production, such as how the structure should be designed or how the production should be scaled.
If you feel that a Machine Learning Engineer position is for you, you should focus on learning more about software engineering practice and MLOps to switch to these careers.
The article How to Become a Machine Learning Engineer by Nisha Arya could also help you kickstart that career path.
4. Business Intelligence
Business intelligence (BI) is an alternative career path for those who still love to gain insight from the data but are more interested in analyzing historical data to inform the business.
BI focuses more on descriptive analytics, where business leaders and stakeholders use data insight to develop actionable initiatives.
To facilitate the analysis, BI uses tools to create dashboards and reports for the business.
Many BI positions require skills such as basic statistics, SQL, and Data Visualization tools such as Power BI. These are skills that people have to learn when they try to become data scientists, so BI would be a suitable alternative career path for those who love analyzing data.
If you want to improve your skills for a BI position, the article Big Data Analytics: Why Is It So Crucial For Business Intelligence? by Nahla Davies would help you.
5. Data Product Manager
A Data Product Manager might be perfect if you want to move into a position with less technicality but still related to data science.
This position prefers a skillset for a strategy to create a roadmap for the data-centric products or services.
The Data Product Manager job focuses on understanding current market trends and guiding data product development to meet customer needs.
Typically, a data product manager should have skills that include business understanding, data technology understanding, and customer experience design.
These skills are necessary if the Data Product Manager wants to succeed in this position.
You can read the article here to understand more about Data Product Manager.
That’s all for today! I hope this helps you understand what alternative career you can choose.
Are there any more things you would love to discuss? Let’s talk about it together!
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