Data science salaries tend to be high than most other ITES jobs. Know more about data science salary and career potential. Stay updated with the latest data science trends.
Data science is one of the most rewarding fields in IT now, globally, and in India. Organizations truly value their data scientists and compensate them highly for the immensely sensitive data platform technicalities and the complex nature of work they handle. The average data scientist salary in India is 818,994 rupees per annum. This number is increasing with more and more MNCs and local corporations investing heavily in human assets specializing in data science. This leads to a massive increase in both the average entry-level data science fresher salary and the salaries of skilled data scientists with more experience. This article will cover the various job roles of a data scientist and their skills to become one. We will also cover the average data scientist salary in India, various data science jobs, a salary that these jobs offer globally, a data scientist’s career opportunities. (Source)
A data scientist’s tasks range from making predictions based on potential trends, assisting in analyzing data and information from various sources, and excavating these structured and raw forms of data to identify inefficiencies and opportunities to provide better solutions for business requirements. They are also tasked with creating models for utilizing the data and data cleaning using various programming languages. Because of data scientists’ importance in IT processes and projects backed by data, organizations are willing to invest highly in data scientists. Skilled individuals who have all the necessary capabilities to function as efficient data scientists offering high productivity and value to the corporation are rewarded handsomely. The amount of data science jobs, the salary of one of these jobs, and the career prospects of data science jobs are the biggest concerns of interested individuals before considering delving into this field.
Table of Contents:
- How to Become a Data Scientist
- Data Science Job Roles
- Data Science Salary Range
- Data Science Career Potential (Includes Free AI & Data Science Salary Report)
- Challenges to Overcome in Data Science Career
- FAQs – Frequently Asked Questions
AnalytixLabs has been providing expansive AI & Data Science courses since 2011, focusing on practical and tailored learning modules and coaching to prepare field-ready data scientists. AnalytixLabs is one of the leading Applied AI & Data Science training institutes in India.
How to Become a Data Scientist
Data scientists help companies with data-centric projects and make effective data-backed decisions. Hence, companies must hire the right personnel for efficient and reliable data science skills. The data scientists assist corporations with manipulating massive amounts of data, creating visual representations, and predicting possibilities and risks. For this kind of sensitive job responsibilities and tasks at hand, data scientists must be skilled in certain areas and have expertise in data science’s fundamental elements. Here are a few areas where a data scientist must be skilled in to gain the confidence of potential employers or corporations,
- Having a strong foundation in mathematical and statistical concepts
- Knowing how to visualize data and create graphical representations
- Data processing skills and being an expert in the manipulation of data
- Proficiency in programming languages and knowing how to use data science tools effectively
Data Science Job Roles
A Data Scientist has many job roles and job profiles that he or she can go for. There are various specialized fields that a budding data scientist can choose, or they might choose to work with various teams in a symbiotic work environment with other fellow data scientists. There are many roles that a skilled data scientist can fill, including the following but definitely not limited to these,
- Data Analyst – Data analysts assist in data preparation, data sourcing, data analysis, and building predictions after gaining valuable insights from the sourced data.
- Data Architect – Data architects are tasked with creating data models based on business requirements and working within data architectures relevant to the business.
- Business Intelligence Developer – This is a data scientist in charge of developing, deploying, and maintaining Business Intelligence interfaces and models using interactive, visually immersive tools.
- AI or Machine Learning Engineer – A data scientist specializing in AI and machine learning, helping in automation and helping machines learn from machine learning models and making them capable of functioning independently.
Data Science Salary Range
According to a study conducted by the reputed U.S. Bureau of Labor Statistics, the average data scientist salary in the US is $100,560. The data scientist salary a fresher gets offered in the United States of America is around $95,000, and moderately experienced individuals are compensated with salaries ranging from $130,000 to $195,000. The average data scientist salary for experienced personnel is $165,000, with the alluring sum of $250,000 being the average compensation for data scientists in managerial or senior positions. Source
According to PayScale, the minimum data science fresher salary one gets offered when joining as an entry-level data scientist in India is ₹342,000. It can range between that and anything up to ₹2,000,000 for skilled human assets. The average data scientist salary for freshers is reported to be around ₹700,000 annually in India. With MNCs and large corporations offering even larger sums, even smaller local organizations and startups offer well-trained data scientists who have no field experience salaries up to ₹500,000 per annum. Data scientists with 3 to 5 years of experience can bag satisfactory salaries, ranging from ₹1,000,000 to ₹1,400,000 per annum.
(Source 1 | Source 2 | Source 3)
Data Science Career Potential
According to the annual report on Data Science and AI trends by the reputed Analytics India Magazine and AnalytixLabs, which has covered all the major prospects of the data science industry in 2021, 2021 will see intelligent machines’ growth hybrid cloud and increased adoption of NLP. There will be an overall increased focus on Data Science and AI.
You can check our annual AI & Data Science Salary Study for 2021 created in association with Analytics India Magazine or the other reports offered for free through this link.
Big Data is forecasted to experience a growth of CAGR of 10.9% from the sum of US$179.6 billion in the year 2019 to a staggering US$301.5 billion by 2023. This will be backed by huge funding of US$4.5 billion by the year 2023 as compared to a lower US$2.7 billion during 2019, which is also an impressive CAGR of 13.5%. Source
Challenges to Overcome in Data Science Career
a. Preparation of data
Data preparation takes a long time and is an exhaustive job that involves analyzing terabytes of data from various sources daily while keeping logs to prevent duplication.
b. Multiple sources of data
The various data sources that data scientists need to access to utilize the data to produce valuable insights require individual data entries and manual data searches, which result in errors and duplications.
c. Security and integrity of data
With cyberattacks becoming increasingly common and confidential data becoming vulnerable, more regulations and standards are setting data scientists back and slowing down their pace.
d. Misunderstanding business problems and ineffective communication with stakeholders
Data scientists face many problems if they start a project that does not have a clearly defined business objective and problem. This is aggravated when the management, clients, or stakeholders cannot grasp models and solutions, which results in the inability to execute their tasks effectively.
e. Misconceptions about the job roles and distribution of work
In many organizations, data scientists are expected to do more than they are supposed to, ranging from cleaning data, retrieving data, building models and conducting analysis, and making predictions. This puts more on a data scientist’s plate than what they can manage alone. An organization cannot efficiently function without having separate individuals specializing in data visualization, data preparation, creation of models, etc.
FAQs – Frequently Asked Questions
Q1. Is Data Science Still in Demand in 2021?
According to the U.S. Bureau of Labor Statistics’ prediction, the data science industry will experience increasing growth, which will lead to the number of available jobs increased by an immense 28% by 2026. This translates to around 11,500,000 new job openings in data science. 2021 has just started, and India has already generated the requirement for 50,000 data scientists. The other countries and corporations are taking similar measures to provide more data science jobs to use data science to develop this field effectively. So yes, data science is still in demand in 2021. Source
Q2. Is Data Science Still a Good Career?
Yes, it’s a great career to consider now and has an even better future with the IT industry regaining momentum again at the double the pace after staggering a bit during the COVID-19 crisis. There are many prospects in the healthcare, automotive, and software development industries, with each predicted to generate 20,000, 5000, and 100,000 jobs respectively in India. Companies like Accenture, IBM, Tata Consultancy Services, and Capgemini offer lucrative salaries and are hiring generously throughout India. It is the same globally with data science being focused on worldwide with the US leading the pack due to housing most of the Big Data companies and Germany demanding many data scientists for their engineering, automotive, and machinery industries to assist production and operations. Similarly, each country has its own requirement for data scientists. The demand or need for individuals trained in data science will only grow with data science applications increasing and technology assisting data science to reach greater heights.
Q3. Can I learn Data Science Without Programming?
One of the main tasks involved in a data scientist’s job includes data mining using APIs, cleaning the data, and analyzing the data with languages like Python. Even though some individuals agree that some data scientists’ roles can be fulfilled without applying or using programming languages, programming languages and programming concepts are very helpful for data scientists to function effectively. Python and R are the most preferred programming languages, with SQL, MATLAB, and Java following closely behind.
The demand for Data Scientists is increasing exponentially every year due to the huge importance companies place on them to help them use data and make data-backed business decisions to boost the company’s effectiveness and profits. Data scientists with expertise and skills in machine learning, data representation or visualization, and data analysis are in high demand. This demand will increasingly rise with the world shifting towards data-centric businesses and services powered by complex data models. If you have any queries or opinions about this topic, drop a comment down below, and we will definitely get back to you!
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