The method of developing, recording, storing and analyzing data is known as Data Science. It is used to effectively extract useful information to gain insights and knowledge about any type of data including both structured and unstructured. Nowadays data science is not only limited to university courses, but you can also study data science courses online.
There are different types of positions for Data Scientists/Analysts, some of which are:-
- Product Data Analyst
This is a common role of a data scientist in many companies, especially those who focus on a specific part of the business or product. A product data analyst works in close proximity with other disciplines such as product managers, designers and researchers. He/she is expected to make their decisions based on what the data and analysis suggest.
Important skills of a product data analyst include:
- Product Sense
- Cross-discipline collaboration
- AB Testing
- Metric Definition
- Data Visualization
- Stakeholder Communication
- Business Intelligence, Analytics & Reporting
The role of a business intelligence analyst is quite similar to that of a product data analyst. Both their roles are focused on serving the analytic and reporting needs of stakeholders. A business intelligence analyst works closely with key decision-makers of the company and is responsible for creating the tools to visualize and report the health of important metrics.
Important skills of a business intelligence analyst include:
- Stakeholder Communication
- Data Visualization
- Setting and Tracking Metrics
- Data Storytelling
- Modelling Analyst
A Modeling Analyst is often found in financial terms such as forecasting. Their role usually involves a clearly defined set of metrics around predictions and causal inference. A modelling analyst is responsible for the development of mathematical models to evaluate or forecast measurements. The role is mostly focused on offline analysis i.e. analysis of historical data instead of real-time data analysis.
Important skills of a Modeling Analyst include:
- Mathematical Modeling
- Statistic Analysis
- Time Series Manipulation
- Hybrid Data Scientist
The raw state of data is in the form of huge tables of logs in a myriad of formats and datasets. The role of a data scientist or a hybrid data scientist is to load, combine, clean and reformat the data sources into one or few tables that can be analysed further for model training. This process of breaking down the data is known as “data pipelining”.
Important skills of a Hybrid Data Scientist include:
- Data Pipelining
- Analytics
- Hybrid Data Visualization Expert
The role of a hybrid data visualization expert is primarily focused on data-visualization-as-a-service to data scientists and other stakeholders. Data visualization is one of the most important aspects of the role of data scientists. Data visualization involves elevating the analysis and maximizing the impact of the curated data.
Important skills of a Hybrid Data Visualization Expert include:
- Data visualization
- Tableau or telling the story of the data
- Careful and impactful dashboard designing
Which Role is Right for You?
All the roles have their own distinguished function. Data scientists play a very vital role in the decision-making process of any company. Whether you are a talented data scientist and interested in driving insights, or if you like being near the latest machine learning models, you will need the guidance of a data science course online. A certified data science course online will help you choose the right role for you because it helps you understand the various platforms available in the data science trichotomy.