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Data Science: 10 Different Job Titles Explained


Data science is one of the fastest-growing fields in the world, and job opportunities abound. However, there are many job positions in the field of data science, these positions require specific skill sets or have very narrow job functions.

To help you sort through all of the options, we have compiled this list of data science job titles with short descriptions so you can find the right fit for your skillset.

1. Data Analyst

A data analyst is someone who works with data sets and tries to conclude them. Often companies will give their data analysts a question to answer, and they’ll go about collecting the data necessary to answer it. Data analysts sometimes help build or choose software for their company’s database or even create dashboards to make the data more accessible.

2. Data Engineer

A data engineer is the most technically complex role on a reporting and analytics team. They are responsible for collecting data from multiple sources, storing it in an accessible way, and preparing it for use by analysts.

3. Machine Learning Engineer

A machine learning engineer has mastered Python programming, understands the principles of machine learning algorithms, knows how to train and evaluate models on real datasets, and can work with a data engineer to build a model that runs on new data when it becomes available. Their work typically focuses on researching new algorithms or applying existing algorithms to new types of problems.

4. Data Scientist

A data scientist is a senior member of a reporting and analytics team. They are responsible for understanding business problems well enough to come up with analytical solutions, designing experiments to test their solutions, analyzing the results of those experiments, and communicating those results to stakeholders.

5. Statistician

Statisticians use statistical analysis to solve real-world problems. They are experts in understanding data and writing algorithms to process it. Additionally, they create new statistical models and processes to analyze data in more efficient ways. A commonly cited example of a statistician is Nate Silver, who used his skills as a statistician to predict the outcomes of presidential elections.

6. Data Architects

Data Architects are the people who build data warehouses, which are organized databases that are intended to be used for analysis. Data Architects work with client stakeholders to figure out what type of database they need and build it to suit their needs.

7. Data Visualization Specialist

A Data visualization specialist’s role is to work with data and information by creating visual aids, such as charts, graphs, animations, slideshows and other presentation formats to make data understandable.

8. Business Analyst

Through insights and data analysis, a Business Analyst assists firms in analyzing their processes, products, services, and systems to enhance current operations and make effective decisions.

9. Database Administrator

This person ensures that the database runs smoothly and efficiently for both its users and its developers.

10. Data Journalist

As a Data Journalist, your role is to take data and make it understandable. You analyze data and then publicize the findings in a way that anyone can understand. You also need to be able to explain what the data means for us as humans.

The most common job roles in data science are listed above, along with more detailed descriptions of what each role entails.

Although there is plenty of overlap between roles, each position tends to focus on a different aspect of data science within the overall field. Therefore, depending on your experience level and career focus, you may find yourself gravitating towards a particular job title over another.

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