Now Reading
How To Crack A Data Science Interview

How To Crack A Data Science Interview

Ambika Choudhury

The data science and analytics sector in India has witnessed a sharp increase in demand for highly-skilled professionals who understand both the business world as well as the tech world. Data Science is considered one of the most lucrative jobs in the industry right now. 

However, the industry is still riddled with a lot of challenges in terms of talent and which is why organisations have started pouring a substantial amount of money in building their data science and analytics team. Organisations regardless of their positions have been using data science and analytics to garner insights from data. 

Need For Young Professionals:

The Data Scientist career is titled as the “Hottest Career of 21st Century” by Harvard Business Review and this position has proved to be one of the most appealing as well as wanted by the job seekers. However, there has been a potential shortage of Data Scientists in the field. The reason behind this is the technological challenges that are limiting the skills of the employees. Most of the senior-level management has started off from software or coding designations since the sector wasn’t evolved enough to encompass the designation of a data scientist.



An entry-level data scientist is someone who has less than four years of experience working as a business analyst with knowledge in Python. The entry-level role also applies to senior software engineers looking for opportunities to work in analytics and machine learning projects.

Basic Guidelines For A Good Resume:

Before we proceed to the interview questions, here are a few tips about prepping your resume and organising some key talking points that would showcase you in a positive light.

  • Make sure you include essential details like email, contact number, and a professional picture.
  • Obviously, mention your educational background
  • Mention the key projects related to machine learning and data science.
  • List down recent and relevant work experience with details about the programming languages/ technology used and direct business outcomes (if applicable).
  • List down achievements like hackathons, bootcamps and certifications.
  • Include Professional Channels like Kaggle, Github, and LinkedIn accounts.
  • Try to keep your resume short and under one page. 

Cracking The Data Science Interview:

Today, this article will take a more in-depth look at what it takes to crack a data science interview for a person with more or less than five years of work experience. Here, we list down 10 important points following which an aspirant will surely achieve his/her dream. 

  • Mastering Programming Language: Talking about the primary skills, for a data science interview one must have a keen knowledge of fundamental topics like distributed computing and data structure, languages like Python, R and SQL. According to a survey, Python continues to be the most popular language in the industry in 2019. Other essential languages falling out of a Data Scientist’s toolbox are R, SQL, SAS, among others.   
  • Implementing Programming Language Algorithmically: After mastering a programming language like Python or R, one must try to implement the language algorithmically. This will not only help an aspirant to understand how to create and deploy the complex machine learning algorithms but also help to master the language more quickly.   
  •  Get Familiar With Production Deployment Environments: Most of the organisations these days have been using the cloud as an infrastructure model. In other words, we can say that the cloud has been ruling the data science space. Popular cloud vendors like Google Cloud Platform (GCP), Azure, Amazon Web Service (AWS) have made it easy for the data scientists to quickly set up a machine learning environment and start working without thinking of the huge pile of generated data. 
  • Getting Hands-on Experience: This is the most crucial part of this journey. Hands-on experience allows for a practical depth of knowledge which will not only help a data science applicant to understand the scenario better but also help to demonstrate the skills. Taking up a data science project and trying to build and develop a model provides in-depth knowledge to the domain where the candidate wants to work on.
  • Your Digital Presence Speaks Louder than Words: The data science community is growing in almost every social media platforms such as Twitter, LinkedIn, Facebook, among others. With everything going digitalise these days, one can start his/her own blog or write on LinkedIn posts where s/he can share the knowledge as well as showcase new skills for the community to get noticed. Besides these, a candidate must also try to participate in bootcamps, hackathons, contribute to open-source projects in GitHub or participate in other such competitions.
  • Showcase Your Knowledge and Know-How About the Industry: Candidates must keep themselves updated with the latest news happening around the space. This will help them to keep the same pace as the emerging technologies. Also, identifying new trends and forward-looking opinions will provide great help in an interview. 
  • Possible Questions Asked: While in a data science interview there are a few possible questions that the interviewer might ask the applicant. For instance, What processes did you make more efficient at work? or can you cite one example which you thought was completely outside the box and helped in turning around the project? The motive behind these questions has the possibility to entail details about the current data science team structure, projects they are involved in and how the right projects are prioritized. 
  • Don’t Forget To Ask Questions: If a candidate wants to be a step ahead than the other applicants, s/he should ask insightful questions. The reason behind this is while asking questions, it helps the interviewer to evaluate the worth of the candidate and how well s/he fits in at the company. 
  • Be Good With the Basics of Data Science: To crack a data science interview, one must take a deep dive into the basic topics such as mathematics, statistics, programming languages, basics of Business Intelligence and of course, the machine learning algorithms.
  • Knowledge of Visualisation: In the journey of data science, one has to have the knowledge of any popular data visualisation tool. For instance, Tableau, Google charts, Qlik, among others are popular among the organisations and knowing how to use them will surely help to be a good data scientist.  

Great Learning provides one of the most in-depth courses with a thrust on Data Science. In order to provide high-quality career-oriented education in the domain of Data Science, Great Learning launched PGP and M.Tech Program in Data Science. The most exciting point about these programs offered by Great Learning is that all of the above-mentioned points can be related to the Data Science courses provided by Great Learning. From learning popular programming languages such as Python, R to exploring the gamut of data through popular tools like Tableau, these programs offered at Great Learning will definitely help you find your spot in the domain of Data Science.

Unlike any other programs, the programs by Great Learning provides a Dedicated Placement Assistance at the completion of the courses. Due to the great industry connection, several leading companies participate in the hiring drives organised for the aspirants of the courses. At the end of the course, there is also a Placement Readiness Evaluation where the aspirants are provided help to prepare for interviews. Some of the companies that have recently participated in the hiring process include Uber, Swiggy, Oyo, Mercedes Benz, Cognizant, among others. 

How Do The Programs Standout

  • The programs offered by Great Learning provides career support to the aspirants through Placement Readiness Evaluation to help aspirants prepare for interviews, on clearance of which aspirants sit for the placements.
  • Learn from leading academicians and experienced industry practitioners in the field of data science.
  • Build knowledge through classroom lectures by expert faculty and doing multiple challenging projects across various topics and applications in Data Science.
  • Great Lakes is the youngest institute in India to receive an AMBA, UK accreditation, and a leader in analytics education.
  • Several leading companies participate in the hiring drives organised for PG Data Science Course aspirants.
  • Earn a Great Lakes certificate and create an ePortfolio to showcase your learning & project.
  • Some of the companies that have recently participated in the hiring process of PG Data Science Program include Uber, Swiggy, Fractal Analytics, Oyo, KPMG, Mu Sigma, Mercedes Benz, Cognizant, Mahindra, Big Basket, among others.

PGP – Data Science and Engineering

The 5-month PGP Data Science and Engineering Course uses a combination of learning methods that include classroom teaching, hands-on exercises, and sessions with industry practitioners. The classes are conducted on weekdays and are assisted by online discussions and assignments. In this course, the applicants will build their knowledge through classroom lectures by expert faculty and doing multiple challenging projects across various topics and applications in Data Science.

Who Can Participate In This Program?

This course is for candidates with 0 to 3 years of experience.

Job Roles One Can Break Into:

This course will help the applicants to prepare for jobs in profiles like Business Analysts, Data Analysts, Data Engineer, Analytics Engineer, Big Data Consultant, etc.

Hands-on Learning:

The course covers the tools and skills sought by leading companies in Data Science. Through the duration of the course, candidates are trained on Python, SQL, Tableau, Data Science and Machine Learning.

Dedicated Placement:

Candidates do receive placement assistance in the Post Graduate Program in Data Science & Engineering. Upon successful completion of the program, candidates would be provided interview opportunities up to 3 months’ post completion of the program. Great Learning also prepares candidates for interviews by providing extensive support in terms of mentoring, CV review, interview preparation etc.

M.Tech in Data Science and Machine Learning

The M.Tech in Data Science and Machine Learning is a 21 months program offered in Full-Time / Weekend-Classroom formats, which enables participants to gain an in-depth understanding of data science and analytics techniques and tools that are widely used by companies. Upon successful completion of all requirements, the participants in this program will earn an M.Tech Degree from PES University. The classes will be held at PES University Electronics City Campus, and Great Learning online platform.

See Also

Who Can Participate In This Program?

This course is for candidates with 0 to 5 years of experience.

Job Roles One Can Break Into:

Data Scientist, Data Analyst, Machine Learning Engineer, Data Science Generalist, etc.

Hands-on Learning:

Through the duration of this course, the candidates will be trained on Python, SQL, Tableau, Data Science and Machine Learning. 

Wrapping Up

The above courses provided by Great Learning are one of the most in-depth courses with a thrust of Data Science and Machine Learning. It is definitely a one-stop solution for the aspirants who want to upskill their knowledge in the field of Data Science and Machine Learning. 

Interested candidates can apply here. 

  1. M.Tech in Data Science and Machine Learning
  2. PGP – Data Science and Engineering 

Provide your comments below

comments


If you loved this story, do join our Telegram Community.


Also, you can write for us and be one of the 500+ experts who have contributed stories at AIM. Share your nominations here.

Copyright Analytics India Magazine Pvt Ltd

Scroll To Top