What are the Technical Skills Required for a Data Science Internship?

7 min readMar 27, 2022


Getting an Internship is something that requires a lot of effort in preparation. Many times we get rejected just because of a silly mistake. No worries we have brought to you an extensive blog in which all the points have been covered. All you need to do is to follow all the suggested steps one by one. Let’s get started.

Let’s check out some skills that are important for a Data Science internship.

  1. Statistical and Probability Skills: If you need an internship in Data Science, then Statistical and Probability Skills are a must. That means you should be familiar with at least the basics of Statistical Analysis including statistical tests, distributions, linear regression, probability theory, maximum likelihood estimators, etc. And that’s not enough! While it is important to understand which statistical techniques are a valid approach for a given data problem, it is even more important to understand which ones aren’t. Also, there are many analytical tools that are immensely helpful in Statistical Analysis such as SAS, Hadoop, Spark, Hive, Pig, etc. so it’s important that you have some knowledge about them.
  2. Programming Skills are also a necessary tool for getting an internship in Data Science. Python and R are the most commonly used languages for Data Science so you should be familiar with at least one of them. Python is used because of its capacity for statistical analysis and its easy readability. Python also has various packages for machine learning, data visualization, data analysis, etc. (like Scikitlearn) that make it suited for data science. R also makes it very easy to solve almost any problem in Data Science with the help of packages like e1071, rpart, etc.
  3. Machine Learning: You should also know basic Supervised and Unsupervised Machine Learning algorithms such as Linear Regression, Logistic Regression, K-means Clustering, Decision Tree, K Nearest Neighbour, etc. Most of the Machine Learning algorithms can be implemented using R or Python libraries so you don’t need to be an expert on them. However, it’s still good if you know how the algorithms work and which algorithm is required based on the type of data you have.
  4. Data Management and Data Wrangling: You need to be proficient in Data Management which involves Data Extraction, Transformation, and Loading. This means that you have to extract the data from various sources, then transform it into the required format for analysis and finally load it into a data warehouse. To handle this data, there are various frameworks available like Hadoop, Spark, etc. Data Wrangling is also an important part of Data Science as it involves cleaning and unifying the data in a coherent manner before it can be analysed to obtain any actionable insights.
  5. Communication Skills: Yes, this is not a technical skill, but good Communication Skills can set you apart as a candidate for a Data Science internship! That’s because while you understand the data better than anyone else, you need to translate your data findings into quantified insights for a non-technical team to aid in the decision making. Another facet of this is data storytelling. If you can present your data in a storytelling format with concrete results and an interesting story then that will automatically elevate your value.

How can I get a data science Internship Off-Campus?

There are several ways to try, just remember that no single method can give you a guaranteed internship. Don’t apply on companies’ websites. If you do, don’t expect to get a reply. Do apply on LinkedIn posts where the author mentions that they are looking for an intern. You can search for such posts by typing keywords like ‘data science intern’, ‘data science internship’, ‘data scientist intern’ etc in the search bar on LinkedIn and choose ‘Posts’. Contact your college alumni who are in high enough positions in tech companies, or have founded their own start-up. Their nostalgia for college will work in your favour and they would definitely want to help you out.

Don’t go for internships where you have to pay. They are simply training programs being sold under the name of the internship. Internshala is a good place where you can apply. Most other internship websites are quite useless and nobody gets any reply after applying.

How to Showcase your Skills to Get a Data Science Internship?

  1. Work on Projects: Projects are a great way to demonstrate your skills in Data Science. And it doesn’t hurt that they are fun to do as well! There is nothing more interesting than analysing a data set to find the correlations between the data and obtain unique insights. There are many dataset sources where you can download and use data sets for free. These include Kaggle, Data.gov, Google Cloud Public Datasets, Global Health Observatory, etc. some of the popular projects that you can try on Kaggle if you are just a beginner include the Titanic Survival Project, the Personality Prediction Project, Loan Prediction Project, etc.
  2. Create a GitHub Profile: It is also a huge plus point in your favour if you have a GitHub profile. Your profile is basically your data science resume that proves you can do what you say! Most hiring managers look at your GitHub profile as a part of the selection process so the more impressive it is, the higher your chances of selection. You should make sure to have clear problem statements, clean code files, and extensive personal projects on GitHub. If you are highly knowledgeable, you could even contribute to some open-source projects to showcase your skills.
  3. Write Online Blogs: They say you have only understood something when you are adequately able to explain it to others. So, consider blog writing an excellent learning tool where you can clarify your own concepts while also teaching something to others. You also get back thoughts and feedback from your readers which only helps you in improving yourself. There are many online platforms where you can write including GeeksforGeeks of course! You could also try out Medium or Quora.
  4. Create Connections on LinkedIn: LinkedIn is a great way to build your professional network and gain more connections. Recruiters also check out your LinkedIn profile as it serves as a digital resume highlighting your skills, experiences, and education. You might even miss out on some internship opportunities if you don’t have a LinkedIn account or if it’s not regularly updated. And if you have a professional network on LinkedIn, you might even get some internship opportunities there!

How Do They shortlist candidates to the hiring for off-campus internships in Websites like Internshala?

Machine Learning internship Shortlisting process in Internshala. Usually, there will be two rounds:

Assignment Round:

They give a Data set and ask you to implement the Machine Learning Algorithms like K Nearest Neighbours, Logistic Regression, Decision Trees, etc and ask you the best Model which gives the best results for that data set.

Example Task Assignment: Please find attached the excel sheet in the following link. This sheet contains the aquaculture water quality variables like Temperature, TDS (Total Dissolved Solids), pH, DO (Dissolved Oxygen) obtained from an IoT device in real-time over a time period. Can you suggest the best ML model which can predict the DO if other variables like pH, TDS and Temperature are known? If yes, can you show the working? Link

Note that the Assignment round differs from company to company, Role to Role.

Interview Round: Note that most of the questions in the interview are related to your previous project or work which you put in your resume. So, make sure that whatever you write in your resume, you should be strong with that project or work. Don’t Include any things in your resume that you can’t Explain.

Some common Data Science interview questions like:

• Tell us a bit about yourself.

• Why have you applied for this internship?

• Why do you want to work in this industry?

• What are your strengths?

• How do you prioritise your work?

• Why do you want to be a data analyst?

• Which area would you prefer to work in and why?

• Which data analysis tools do you frequently use?

  • Tell me about the most difficult data analysis project you’ve done.

This was just to give you a brief idea of the process so that you can be prepared with your unique answers. There can be variations like the interviewer might ask you to code in front of them, or there might be many rounds of interviews. But you don’t need to worry at any step. Just stay calm and look for the solutions and we hope you crack the interviews and get the internship. Good Luck for your future endeavours. Do visit the official website of AlgoZenith if you wish to master Data Structure and Algorithms for your future Internship/Job tests.

Do let us know in the comments if you liked the content also do check out our blog series on Finance and Product Management. Do check this blog if you are searching for an Ultimate guide for your Job/ Internship. Stay tuned for more such blogs. You can also check out the previous blogs of this series on Everything about Data Science, What is Machine Learning and How to approach a Data Science project for a beginner. Keep Learning Keep shining.