8 Great Data Science Paths You Need To Know About
What is Data Science?
Data science is basically an answer to what? What is my data saying? To derive the answer, we use a number of tools and techniques including math and visualization.
Since data science is a very vast domain, it’s simply not possible to cover each and every way to learn each domain. Therefore you would need to be very specific and only develop a specialization in 1 to 3 areas depending upon your exposure to the market.
About Me
My name is Muhammad Osama, and I have been working as a data analyst for the last 2 years having worked at global companies such as Unilever and British Tabacco. I have worked with different tools such as SQL Server, Power BI, Qlikview, and Excel.
You can reach me at muhammad.osama@cybercode.ca
https://www.linkedin.com/in/mosamaasif/
Paths In Data Science
Data Scientist
This role is responsible for deriving facts and figures from different datasets which can either be structured or non-structured datasets. In some cases, they also does visualization.
Data Architect
This role is responsible for setting up the database within an organization. These databases range from Hive, SQL Server to MongoDB etc.
Data Engineer
This role is responsible for getting the data into the organization’s database, this process is referred to as building a data pipeline. Data Engineer is also referred to as an ETL developer, they work with SQL, Python, and many ETL tools such as SSIS, Microsoft Automate, or even Pentaho.
Data Science Manager
Data science manager is a very senior position, they are responsible for communicating with different stakeholders of the business. Therefore, it is their job role to understand the nature of the business and upon gathering the business requirements, their job role is to lead the team in the right direction.
Statistician
This is one the oldest professions in this field, this person is responsible for using statistics to determine the facts and figures about the data. This includes tasks such probability, A/B testing and creating equations.
Machine Learning Engineer
This person is responsible for developing mathematical equations for regression to use different algorithms such as K nearest neighbor and random forest to answer different questions related to the business requirements.
This includes training the computer to understand fraud and patterns in data etc. Nowadays, these different algorithms are implemented with the help of different software such as databot, Azure Data Studio.
Data Scavenger
As the name suggests, this person is responsible for pulling the data from the web. This can range from scraping simple data from a page to exploiting the website to consume data from the website that’s using a web-service.
Data Analyst
This person is responsible for cleaning, validating, and transforming data so that the data can be used to develop charts and graphs by the aid of which business can make key decisions based on key facts such as how many items are in-stock, categories with the highest sales, and most products with the lowest sales. They use tools such as Power BI, QlikView, and different databases such as SQL Server and Oracle.
Which Path To Take?
Since there are so many paths, you might feel overwhelmed at which one to take. So don’t worry about it. They are all terrific fields. What I would suggest is that you develop a specialization in a single field and stick to it.
Because even one field can be overwhelming, take for example data analysis, you would need to learn BI tools such as Power BI but there are so many tools out there such as Tableau, Data studio, and QlikView. So even if you specialize in one field, you would need to be very specific and learn new tools as you need to use them, not prior, otherwise it would be really difficult to learn.