Data has become one of the most important resources in the digital economy. Companies worldwide are working to find the right talent to leverage the power of data. As a result, jobs in data have become highly in-demand and offer promising career opportunities.
As explained in previous articles, data is popular for several reasons. First, the data industry has grown rapidly in recent years, and it continues to expand. Companies find difficulties in finding the right talent to make sense of their data. Data professionals are among the best-paid workers in the digital economy.
Here are some key data roles in the industry:
Data Analyst
Data Analysts are responsible for collecting, cleaning, and preparing data for analysis. They have a deep understanding of the data analysis process and report insights to help solve specific business problems.
Anyone interested in becoming a data analyst should develop skills in database querying (SQL) and learn a programming language like Python.
Data Scientist
Data scientists define the questions their teams should ask about the data and design strategies to find the answers. They share many skills with data analysts but tend to be more senior and focus on:
Big Data
Advanced data analysis techniques, such as machine learning
Big Data is often associated with AI and Machine Learning.
AI stands for Artificial Intelligence (sometimes Augmented Intelligence) and refers to machines that behave in ways that, until recently, required human intelligence.
Machine Learning is a type of AI that learns from data to make predictions.
Today, most AI applications are actually Machine Learning solutions, and when people talk about AI and Machine Learning, they may be referring to the same thing.
Machine Learning Engineer
Machine learning engineers are responsible for designing, optimising, and deploying machine learning models that can learn from data. They are highly technical professionals with a solid background in math and coding.
Python is a good programming language to start with if you're interested in machine learning.
Data Engineer
Data engineers lay the foundation for a smooth data analysis process. They manage the design and maintenance of a company’s database architecture and data processing systems.
Anyone interested in becoming a data engineer should start by learning SQL and a programming language like Python or Java.
Today, the entire data analysis process can take place on the internet, or as it's often called, "in the cloud". Having cloud technology skills will set you apart from the competition.
Which tasks can be done in the Cloud?
Build and deploy machine learning models
Clean data
Collect and store data
Roles Beyond Data Science Positions
While coding skills are required for the technical data roles we've covered, there are also many opportunities for people from non-tech backgrounds, such as:
Data product manager
Data strategy consultant
Data ethicist
Technical writer
Taking one of these roles can be a great gateway to breaking into the data science industry.
Cheers, Irina 😊