Data Science Career Path
  • Introduction
  • The aim of this guide
  • Who is an entry-level Data Science Professional?
  • Data Science Entry-Level Job List 
  • Data Analyst
  • Statistician
  • Database Administrator
  • Data Visualization Expert
  • CRM Data Analyst
  • Research Data Analyst
  • takeaway

 

Introduction 

Many people have heard about data science and its potential but don’t know where to begin or what exact career path they would want to choose. 

There are many ways to begin your journey in data science. A great way to do this is by choosing an industry-relevant online program curated and taught by industry experts who will give you an in-depth understanding of the concepts, algorithms, and methods used in data science while exposing you to many of the real-world applications that go along with these.

We will give you a broad overview of all of the different positions and career paths available to someone who wishes to enter the field of data science and help you start building your own unique success story within this domain. 

 

Aim

The idea behind this guide is to provide advice and assist you as you start your journey in the field of data science. This guide covers what level of abilities you would need to equip yourself with and what work experience level you need to accomplish to go after specific job positions as a Data Science Analyst. 

The guide also provides in-depth information on various data science jobs, their requirements, pay scale, and a brief overview of what they involve. By the end of this blog, you should be able to make an informed decision on which career path you would want to head for in the field of data science-based on your skill-set, experience level, and career plans.

 

Who is an entry-level data science professional?

Data science is a very broad field today, and a large number of people from diverse professional backgrounds are trying their hands at it. It is common to find Data Scientists coming for all industry verticals, from education to healthcare, and everything in between. 

Data science is heavily reliant on mathematics, statistics, and programming languages (like R and Python). Thus, a basic understanding of the language associated with data science is a must-have for anyone who wants to be an entry-level Data Scientist.

In short, if you are interested in playing with numbers and coding is on your radar, then it is easier to start at an entry-level as a Data Scientist. 

Graduates with 1-4 years of experience as Data Scientists can earn from up to ₹540k to ₹747k per annum.(Source)

 

Data Science Entry-Level Job List

  1. Data Analyst

Data Analysts are people who understand numbers, statistics, and data – to present them in a way that everyone can understand. The field of data mining includes knowledge of programming languages, such as SQL and Python, to extract relevant information from data sets.

Average earnings of a Data Analyst in India

  • 1-4 years of experience is ₹427k per annum.
  • 5-9 years of experience is ₹694k per annum.
  • 10-19 years of experience is ₹929k per annum.
  • 20+ years of experience is ₹2 million per annum.

(Source)

According to the 2017 Robert Half Salary Guide, financial analysts at an entry-level can make from up to $52,700 to $66,000 per annum based on bonuses and commissions. 

The average salary for a Data Analyst in India is ₹441, 327 per annum.(Source)

  1. Statistician

The basic responsibility of a Statistician includes the collection, analysis, and presentation of statistical data to the senior management in order to identify trends and patterns that link them to other information. 

The responsibilities of a Statistician are to implement the planned information, decision-making, conveying discoveries to companies, and implementing the hierarchical technique. Employment for Statisticians is expected to grow 30% by 2028. It is important to have analytical skills, technical skills, knowledge of algorithms, and strong communication skills.

The per annum salary range for a Statistician with 0-5 years experience can go up to ₹7,97,508. 

Senior Statistician with years of relevant work experience can earn a salary between 3.2 Lakhs to 26 Lakhs per annum.(Source)

The national average salary for a Statistician in India is ₹4,09,615 per annum.(Source)

  1. Database Administrator

A Database Administrator is a person who is in charge of monitoring, maintaining, and supporting the database of a company. They are also responsible for retrieving data from a database. The primary responsibility of a DBA professional is to maintain data stability. 

A Database Administrator must have experience with a wide array of database management products such as Oracle-based software, SAP, and SQL, having a degree in Computer Science and practical field experience. Additionally, related IT certifications prove to be beneficial to a DBAs career.

Data Analysts who are in charge of quality get a high-paying job due to their experience. 

Database Administrators, on average, make about $77,428 annually in the United States, while Senior Database Administrators, on average, earn close to $104,000 per annum. With more work experience, the average annual income for a Data Analyst can go up to $115,000.(Source Source)

  1. Data Visualization Expert

Data Visualization Experts are in charge of creating analytics dashboards, graphical representations of data to identify any patterns and trends.

Data Visualization Analysts convert data in a visually appealing way for users to understand. They make information understandable and easy to interpret. You must have excellent analytical skills. You need to be able to work with the magnitude of data and make it functional, handy—and also have an understanding of math.Data Visualization Experts can work for big Fortune 500 companies or other consulting firms. The average salary for a Data Visualization Specialist in India is ₹8,89,679 per annum.(Source)

  1. CRM Data Analyst

CRM Data Analysts study trends and patterns in customer behaviour to build a customised marketing strategy that will effectively reach out to customers. They focus on recurring business as well as constantly researching new opportunities for growth with an aim to increase revenue.

CRM Data Analysts need to be good at managing information and possess great writing skills. You can also work remotely from home, which is a plus. 

Data is important to every business. Having a strong Data Analyst on your side can be the difference between losing or gaining a customer. According to Indeed, the average salary for a CRM Data Analyst in India is ₹6,08,780 per year. That’s huge considering that most people don’t know what a CRM is.

The minimum qualification required for a CRM Data Analyst is an MBA degree. A few employers may accept a Bachelor’s degree in one of the numerous subjects, such as business, internet marketing, accounting, or computer science.

The national average salary for a CRM Data Analyst in India is ₹4.2 Lakhs per annum.(Source)

  1. Research Data Analyst

The Research Data Analyst uses the power of Big Data analytics to arrive at conclusions about a given business problem. They usually work in teams with other analysts and may use statistical tools for finding patterns in consumer behaviour, customer demographics, or market trends.

The minimum qualification needed is a graduation degree. 

The national average salary for a Research Data Analyst in India is ₹₹3,47,616 per annum.(Source)

 

Takeaway

A career in data science is a smart move, as the demand for data scientists and analytics professionals is growing. It’s like job security insurance for you and your career.

The data science career path gives you the opportunity to make a major contribution to critical ongoing research in this field. It is trendy and pays well. Moreover, data is expected to be the turning point on which the entire economy will run.

Data science specialists are needed in every industry, including healthcare, technology, manufacturing, and business. Job opportunities are indeed growing because companies need people who understand the value of data and how to use it effectively to transform their businesses.