• Sanjay Kumar

Data Science Internship

Updated: Jan 17

Data Science Internship - Datahod

Table of Content

What is Data Science?

Data Science Definition:

Introduction: Data Science Internship

Other Technical Skills Required to Become a Data Scientist Include:

Need for Data Science Internship

How to Solve Real-World Projects

Why You Should Choose a Data Science Internship:

How to Apply for Google Data Science Internship?

What is Data Science?

Data Science is the art of mixing data inference, data collection, designing algorithms, and a technology essence for providing results to complex business problems. The role of data science is not just limited to business solutions rather it is getting used in healthcare, robotics, stock market, agriculture, sports, and many other ways.

Less than 0.5 percent of the data we generate is ever used or analyzed.

At last, the key element is data that emerged from the billions of raw data sets produced by social media, enterprises, data warehouses, industries, the aviation sector, customers, FinTech, and many other platforms. Now, this data needs to get mine so that we can create advanced solutions from it. Here comes the role of data science which is the best solution for providing business values by fetching useful insights from it.

Data Science Definition:

Data Science is the concept of collecting, storing, and analyzing data (structured or unstructured) for extracting useful insights from it.

Last summer when my nephew started looking for an internship program to boost his career, I suggested him for data science as the best decision to start with. It is a field that is continuously evolving. After gaining years of experience while working on machine learning, big data, analytics, and IoT-like technologies, I figured out data science is a key player in the market. Most of the startups and big organizations are already working on data science to enhance their operations. Thus, the demand for skilled professionals and data science interns are rising at a continuous pace.

Almost 10 percent increment in data access can lead to the $65 million increase in income.

At that time, I realized that the data science internship positions are especially available for students preparing to start their careers in an IT organization. Thus, I suggested to my nephew who was an undergraduate to prepare himself to manage the responsibilities of a data scientist.

Almost 40,000 searches are performed over Google every second. It made it to 1.2 trillion per year.

It was the overall experience I gained over the past few years by hiring data analysts, data scientists, and interns for various kinds of organizations. Many people think of a data science internship as a small role, but believe me, it avails a significant experience for a candidate who can further emerge as a big barrel of belief, confidence, and knowledge.

Market Segment - Datahod
Market Segment

Introduction: Data Science Internship

Before I tell you how the whole recruitment process for hiring data analysts and data science internships is performed, I want you to understand the role of a data analyst in the industry. Then, you will surely understand how to get an internship. I will also explain how it differs from the data scientist as you may have heard about these terms repeatedly.

Generally, there are three roles available behind these positions which are the business analysts with less technical work, highly skilled and technical data analysts and the last one is data scientists which are the most technical persons among all three.

1.7 MB of new data will emerge every second per person by 2020.

In big organizations, the business analysts and data analysts are two different positions while in smaller organizations these positions can be a little blur.

The main role of business analysts is to focus on the existing analyzed information so that they can provide a solution to complex business problems. They test the historical information to recognize trends and become a decision-maker. But, they are not responsible for creating data models or making predictions over this information. They are limited to tools like SQL, Tableau for visualization or Excel, etc.

Data Explosion - Datahod
Data Explosion

A data analyst is responsible for analyzing existing data sources for providing solutions to complex business problems. They are involved in strategic information projects along with data scientists. Thus, they require predictive modeling for performing such operations. So, starting your data analyst journey can be perfectly aligned by enrolling in a data analyst internship program. Data analysts are generally aware of any of the scripting languages such as R programming, Python, including the command on various visualization tools, SQL, and Excel.

Other Technical Skills Required to Become a Data Scientist Include:


To be a data scientist you must be aware of programming skills like R, Python, SQL, Perl, etc. The commonly used language for data science in Python and R. These languages are used for removing missing columns, data cleaning, structuring, etc. All the data sets are categorized and then stored in a proper format. For beginners, the most important skills for getting a data science job are listed below:

Glassdoor  Economic Research - Datahod
Glassdoor Economic Research

Analytics Tools:

A data scientist should have knowledge about analytics tools as these are the main requirement of data science. Analytics tools are to be used to extract or analyze the valuable data from the structured data sets. SAS, Hadoop, Hive, and Spark are the analytic tools that are mostly used for this purpose. To be a data scientist you must have skills regarding the same and you can enroll for some certification course for this.

Working with Unstructured Data Sets:

A data scientist needs to be able to maintain and organize unstructured data. Only structured data can be used for further processing. Structuring data is a basic and crucial step. The results of the whole process depend on the data. So it is required to organize all the unstructured data coming from various sources.

Big bad data costs $600 billion per year to US businesses only.

Non-Technical Required Skills

Apart from technical knowledge, a data scientist should have a business, communication, or domain skills. These skills are not related to qualification or certification courses. Some of the non-technical skills are mentioned below:

Strong Business Skills:

For being a data scientist, you should have strong business skills. Otherwise, you will not be able to develop a perfect business model. For generating a business model, you must know how and where to use the element.

Your technical skills will not work here as you won’t be able to design business strategies, problem solutions, and plans for business growth. If you are having complete business skills then you can take your company on a successful path and help in exploring the business with new ideas.

Communication Skills:

A data scientist can perform his role very well if he is good at communication and understands things clearly. You can make your point clear to the customers even if they are not from a technical background. Then you will be beneficial for your organization’s growth. Therefore good communication skills are needed not only for data scientists but for all the employees in the company.

Data Intuition:

It is a highly significant skill that is required in a data scientist. It includes the estimation and perceiving of data patterns that are not observed on the surface. Exploration of the data sets and designing the patterns makes adds a plus point in data scientist performance. This skill can be achieved only with experience.

Need for Data Science Internship

The data science internship is a necessary thing after the course or certification completion. In this, you will get hands-on experience by working in an organization. You learn how companies work with big data and how to develop models to organize the collected data. The work in an organization is quite complex than the study because here you need to deal with real-time business problems. Let’s check out some important needs for the data science internship:

How to Solve Real-World Projects

During the internship, you will learn to deal with real-time problems. You work on real-world projects which add to your experience. You learn how to work on a complete data science life cycle including problem-solving, developing models, etc.

Most of the process includes data cleaning means removing unwanted data or missing values. You will understand and find solutions for the domain and real business problems. You do research and work with experienced data scientists. You will learn the alternate methods to solve a single problem and then how to find out the best solution.

Why You Should Choose a Data Science Internship:

While choosing your career to start with data science, the first question which strikes in your mind must be what are the benefits? Well, the data science market is trending at an unstoppable pace. It is getting used in almost every industry. Its overall market is expanding with a CAGR of 29 percent per year. Let’s figure it out in the below chart:

Data Science Market - Datahod
Data Science Market

Attractive Financial Package

These days, the data scientist is one of the highly paid jobs. In the US, the salary of a data scientist is experienced to be around $105,000 annually. It also includes additional benefits provided by the organization. Data scientists can be more surgeons if they are experts in their work. If you are working on the manager rank then you will feel yourself at the top position.

Huge Job Opportunities

Lots of job opportunities are available for skilled people. If you are capable you can get the best job as the demand for data scientists is growing day by day. In this world of technology, there are lots of options for talented and skilled candidates. Several seats are vacant because of the lack of skills in a particular field.

Lack of Competition

Several professionals want to step into data science as they know the chances of growth in this. Still, there is less competition in this field as some are not aware of the success and some are not capable of doing it successfully. Candidates from finance and accounts backgrounds are preferred by employers for data extraction and mining.

Abundance of Positions

Very few candidates have the capacity to learn the data science and implement is thorough. As compared to other IT sectors, data science is less saturated. This means only the skilled person can get the best position. This field has a number of requirements but has fewer eligible candidates.

Data Science is Versatile

Data science is required to manage the big amount of present data. The main area of data science implementation is health, e-commerce, and banks, etc. You will get a variety of opportunities where you can choose your job sector.

Data Science Makes Data Better

With data science, the whole data can be maintained in an organized way so that it can be used in the future. You can take business decisions on the basis of previously collected data. Data scientists deal with several types and a large amount of data which helps in the company’s growth.

How to Apply for Google Data Science Internship?

Google is a big brand name to start with. Because at Google, they always find smart brains capable of solving the hardest problems in simple ways. You may have heard about Google that its hiring process is hard. But don't lose your hope, if you got the talent, start with google by following these steps:

Open Google jobs using: Search Jobs - Google Careers In the left tab select internship. You can also select a city or location from the right tab. You can also set email notifications so that you will get notified once there are other jobs.

Applying for an internship at Google isn’t the last option. There are many other companies including startups like Haptik, Appstret, Loginext, Social Cops, Mad Street Den, etc; that hire data interns or you can go through Coursera internship and many other programs. You can get a chance here also. They usually hire passionate candidates. Once you are finished with the internship, there is a 90 percent chance that you will get the job at the same place else there are millions of other opportunities available for potential candidates in the market. Must Read Datahod Popular Content 9 Best and Free Machine Learning Courses from World-Class Educators

Thanks for Making it to the end

Thus, you can see that data science jobs are the hottest job for the year 2019-23. So if you want to get a data scientist internship in 2019, my suggestion is:

  • Learn all the required skills.

  • Get a hands-on experience over a project to showcase your skills. You can add these projects to your resume.

  • Apply for internships.

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