From gaming to e-commerce, well-nigh every industry has seen the significant influence of a data scientist. Practically, data scientists can be considered Iron Man for their team.
While we are all familiar with Iron Man and his power in Marvel, many are unaware of how data scientists work in the ever-evolving corporate world and how they aid in making informed decisions.
So here in this article, we will walk you through the responsibilities of a data scientist & different types of data scientists that are in demand.
What does a data scientist do?
The data scientist role combines the use of several traditional and technical jobs, including mathematician, scientist, statistician, and computer programmer, and interprets the large amounts of raw data that is drawn from multiple sources and converted into accessible formats so that it is easy to interpret & make decisions.
Now, let’s take a closer look at different types of Data Scientists:
15 Types of Data Scientists Roles
Operations Data Analytics
| Role | Skills Required | Tools | Industry |
| Analyzing operations data to improve business processes | Data analysis, data visualization, SQL, business acumen | Python, R, SQL, data visualization tools such as Tableau or PowerBI | Operations departments in various industries |
Research Data Scientist
| Role | Skills Required | Tools | Industry |
| Designing and conducting research studies | Research design, data analysis, machine learning, data visualization | Python, R, SQL, data visualization tools such as Tableau or PowerBI | Research departments in various industries |
Vertical Expert
| Role | Skills Required | Tools | Industry |
| Analyzing industry-specific data | Domain knowledge, data analysis, industry-specific tools and technologies | Industry-specific tools and technologies, data visualization tools such as Tableau or PowerBI | Various industries |
Data Strategist
| Role | Skills Required | Tools | Industry |
| Developing and executing data-driven business strategies | Data analysis, business strategy, data visualization, project management | Python, R, data visualization tools such as Tableau or PowerBI, project management tools such as JIRA or Asana | Various industries |
Data Architect
| Role | Skills Required | Tools | Industry |
| Designing and maintaining data architecture | Data architecture, database design, cloud computing, software engineering | Python, R, database management tools such as SQL Server or Oracle, cloud computing platforms such as AWS or Google Cloud | Technology, data-driven companies |
Cloud Computing Expert
| Role | Skills Required | Tools | Industry |
| Designing, deploying and managing cloud-based systems and data | Cloud computing, software engineering, data management | Cloud computing platforms such as AWS or Google Cloud, software engineering tools such as Git | Technology, data-driven companies |
Cybersecurity Data Scientist
| Role | Skills Required | Tools | Industry |
| Analyzing and interpreting data to improve cybersecurity and prevent cyber attacks | Cybersecurity, data analysis, machine learning | Python, R, machine learning frameworks such as TensorFlow or PyTorch | Technology, finance, and various other industries |
Data Visualization Expert
| Role | Skills Required | Tools | Industry |
| Designing and creating visual representations of data to communicate insights | Data visualization, data analysis, design | Data visualization tools such as Tableau or PowerBI, design tools such as Adobe Creative Suite | Various industries |
Data Mining Expert
| Role | Skills Required | Tools | Industry |
| Extracting valuable insights from large datasets | Data mining, machine learning, data analysis | Python, R, machine learning frameworks such as TensorFlow or PyTorch | Various industries |
Data Warehousing Expert
| Role | Skills Required | Tools | Industry |
| Designing and maintaining data warehousing systems | Data warehousing, SQL, data management | SQL, data warehousing tools such as Snowflake or Amazon Redshift | Technology, data-driven companies |
Data Quality Analyst
| Role | Skills Required | Tools | Industry |
| Ensuring the quality and accuracy of data | Data analysis, data management, SQL | SQL, data analysis and management tools | Various industries |
Digital Analytics Expert/Consultant
| Role | Skills Required | Tools | Industry |
| Analyzing digital data to inform business decisions and improve digital strategies | Digital analytics, data analysis, project management | Digital analytics tools such as Google Analytics or Adobe Analytics, project management tools such as JIRA or Asana | Digital marketing, technology companies |
Spatial Data Scientist
| Role | Skills Required | Tools | Industry |
| Analyzing and interpreting geographic data | Spatial data analysis, GIS, data visualization | GIS tools such as ArcGIS or QGIS, data visualization tools such as Tableau or PowerBI | Various industries including real estate, urban planning, etc. |
Business Analyst/Intelligence Analyst
| Role | Skills Required | Tools | Industry |
| Analyzing data to inform business decisions | Business analysis, data analysis, project management | SQL, data analysis and management tools, project management tools such as JIRA or Asana | Various industries |
Actuarial Scientist
| Role | Skills Required | Tools | Industry |
| Applying mathematical and statistical methods to assess financial risks | Actuarial science, mathematics, statistics | Actuarial science software, statistical analysis tools such as R or SAS | Insurance, finance industries |
Conclusion
The key to success as a data scientist is possessing the right skill set and expertise, which may be developed through data science certification courses. So, if you want to be a remarkable data scientist, enroll in a data science certification program and begin your journey.
That being said, just remember that these different types of data scientist roles are not exhaustive; additional comparable roles will arise in the future based on demand and the intricacy of the role.
Thanks for posting, keep adding more valuable content.