Career in Data Science

GUPTA, Gagan       Posted by GUPTA, Gagan
      Published: June 9, 2021

Enjoy listening to this Blog while you are working with something else !


Areas of Expertise in Data Science

The analytics market is booming, and so is the use of the keyword - Data Science. Professionals from different disciplines are using data in their day to day activities, and feel the need to master the start-of-the-art technology in order to get maximum insights from the data, and subsequently help the business to grow.

To be a Data "something", you need to have a passion, and zeal to play with data, and a desire to make digits and numbers talk. It is a mixture of various things, and there are a plethora of skills one has to master. The list of skills often gets overwhelming for an individual who could quit, given the enormity of its applications, and a continuous learning mindset in the field of Data Science demands.
'What sort of personality makes for an effective Data "Something"? Definitely curiosity ! The biggest question in data science is 'Why?' Why is this happening? If you notice that there's a pattern, ask, 'Why?' A natural curiosity will definitely give you a good foundation.'

1.) Data Engineering & Data Warehousing

Job Titles: ETL Expert, Data Engineer, Database Developer, Data Analyst, DWH Developer, DWH Architect. Salary Range: $66k - $141k

Data engineering is a set of operations aimed at creating interfaces and mechanisms for the flow and access of information. Within a large organization, there are usually many different types of operations management software: ERP, CRM, production systems, and more. The process of moving data from one system to another, be it a SaaS application, a data warehouse (DW), or just another database, is maintained by data engineers. A data warehouse is a central repository where raw data is transformed and stored in query-able forms.

2.) Data Mining & Statistical Analysis

Job Titles: Data Scientist, Business Analyst, Statistician, Data Mining Analyst, Analytics Manager. Salary Range: $66k - $145k

Statistical Analysis and Data Mining addresses the broad area of data analysis, including data mining algorithms, statistical approaches, and practical applications. Topics include problems involving massive and complex datasets, solutions utilizing innovative data mining algorithms and/or novel statistical approaches. Data mining is a multi-faceted process. It is true that statistical elements are utilized in the functions of data mining, including classification, clustering, regression and association.

3.) Cloud and Distributed Computing

Job Titles: Cloud - Solutions Architect / Network Engineer / Automation Engineer / Security manager, Platform Engineer. Salary Range: $82k - $177k

Simply put, cloud computing is the delivery of computing services-including servers, storage, databases, networking, software, analytics, and intelligence-over the Internet ('the cloud') to offer faster innovation, flexible resources, and economies of scale. Cloud Services can be : IaaS, PaaS, SaaS or serverless.
Distributed computing is a model in which components of a software system are shared among multiple computers. Even though the components are spread out across multiple computers, they are run as one system.

4.) Database Management & Architecture

Job Titles: DBA, Database Architect, Oracle Consultant, DB Coordinator, DB Analyst. Salary Range: $61k - $142k

This role is responsible for designing, deploying, and maintaining databases in support of high volume, complex data transactions for specific services or groups of services. It refers to the actions a business takes to manipulate and control data to meet necessary conditions throughout the entire data lifecycle.

Our On-Premise Corporate Classroom Training is designed for your immediate training needs

Career in Data Science
Career in Data Science

5.) Business Intelligence

Job Titles: BI - Engineer / Developer / Analyst / Consultant, Data Strategist, CDO, Director BI, Big Data Architect. Salary Range: $87k - $161k

Business intelligence (BI) is an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance. BI technologies provide historical, current, and predictive views of business operations.

6.) Machine Learning

Job Titles: ML Engineer, AI Specialist, Cognitive Developer, Researcher, CDS, Data Scientist. Salary Range: $74k - $167k

Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. Machine learning is the science of getting computers to act without being explicitly programmed. It is here, we make the "Data Robots".

7.) Deep Learning

Job Titles: Deep Learning Expert / Engineer / Architect, Principal Data Scientist. Salary Range: $87k - $232k

Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. aka deep neural network. DL is inspired by the structure of a human brain and neurons.

8.) Natural Language Processing

Job Titles: Chatbot Architect, Principal NLP Engineer, AI Developer, NLP Research Engg. Salary Range: $110k - $172k

Natural Language Processing, usually shortened as NLP, is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language. The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable. Chatbots, Siri, Alexa and Cortana are good examples.

9.) Data Visualization & Presentation

Job Titles: Data Viz Engineer / Developer, Software Developer, SAS Engineer, Tableau Engineer. Salary Range: $56k - $211k

Data visualization is the visual presentation of data or information. The goal of data visualization is to communicate data or information clearly and effectively to readers. Typically, data is visualized in the form of a chart, infographic, diagram or map. Being able to present data in a visually appealing way has become part of almost every business analyst and data scientist role. When these focus area becomes an actual role in a company, their main responsibility includes creating BI solutions for teams and customers based on specific business requirements and use cases.

10.) Domain Specific Analytics

Job Titles: Master Data Domain Lead, Domain Analyst, Domain Expert, Business Analyst, Data Governance Analyst. Salary Range: $81k - $182k

If you studied BFSI, Healthcare Defence or something that requires domain-knowledge expertise to analyze, you might opt to look into simple analyst positions within organizations in these industries. Again, the technical expertise of these roles will depend on the expectations of the company hiring and the tools they use.

Our On-Premise Corporate Classroom Training is designed for your immediate training needs


Nobody ever talks about motivation in learning. Time flies, mostly if you've been stuck at home for a year due to nationwide lockdown restrictions.

To me, my love for Data Science is driven by my love for challenge, my curiosity, and my drive to turn :

- Data into Information
- Information into Knowledge
- Knowledge into Project oriented Actions

So why does the discipline of Data Science appear to need so many skills? A quick job search containing the words 'data' and 'science' will give you an insight.

How to get motivated

At the beginning of your journey, it is really important to have a plan. To make a plan you will first need a goal. In the face of rapidly changing technology within data science, and job roles and requirements changing regularly, I believe it is best not have a goal that is tied to a specific job title. By the time you get there that job may no longer exist.
Instead your goal should be a purpose, in other words, think about what it is that you want to be able to do. For example, my goal when I was learning data science was to 'make a positive impact with data'. In order to make the biggest impact in the shortest possible time frame, my learning became focussed around the applied side of data science.

How to stay motivated

Once you have your goals set and your curriculum determined you need some way to remain motivated. I recommend doing three things:

Write down your goals and refer back to them often.
To ensure that the skills you are learning will help you to reach your goal as quickly as possible it is important to refer back to your long term goal on a regular basis. Whenever you start to learn something new check-in with your goal and ask yourself 'is this relevant?'. This will ensure that you are always learning skills that are strictly relevant to your long term goals.

Create a roadmap.
When designing your curriculum it is a good idea to document it somewhere. Roadmap, consists of a long list of skills on a sheet with a scoring system. Once a month you should score yourself against this list of skills and proficiencies and compare this to previous months. When you are following a course often you can get a sense of satisfaction from ticking things off and getting badges and levels. Scoring yourself on the roadmap shall give you both a similar sense of satisfaction and a way to celebrate your success. A great motivator for learning!

Take a practical first approach to learning.
As soon as you feel able to I recommend putting the skills you are learning into practice. You can do this in a variety of ways including entering machine learning competitions such as Kaggle, creating your own data projects from public data sets or contributing to open source projects. Being able to build things that work will give you an enormous sense of satisfaction and will be far more motivating than any amount of box-ticking ever will.

Disclaimer: Salary Ranges are picked up from

Support our effort by subscribing to our youtube channel. Update yourself with our latest videos on Data Science.

Looking forward to see you soon, till then Keep Learning !

Our On-Premise Corporate Classroom Training is designed for your immediate training needs

Career in Data Science

Corporate Scholarship Career Courses