Common Interview Questions for Data Scientists

Companies seek good employees, as much as employees seek inspiring employers. Microsoft and many other firms have released videos on how you can prepare for a data science interview. In addition, you can strengthen your technical foundations with a certificate course in Data Science or a Master’s in Data Science that can help you stay up-to-date with the demands of the industry. 

Here’s an illustrative list of questions asked in job interviews for the role of a Data Scientist. It can help determine the learning goals for a student in this field.

Common interview questions that are related to Data Science:

• What is the workflow in a Data Analytics project?
• What is the difference between Data Science and Data Analytics?
• What do you mean by logistic regression?
• Name three types of biases that can occur during sampling.
• What do you mean by prior probability and likelihood?
• What are the three disadvantages of using a linear model?
• When is resampling needed in analytics?
• List out the libraries in Python used for Data Analysis and Scientific Computations.
• What is the aim of conducting A/B Testing?
• Which language is best for text analytics? R or Python?
• Name various types of Deep Learning Frameworks.
• Name commonly used algorithms in Data Science.
• What do you mean by univariate analysis?
• What algorithm behind e-commerce websites shows you ‘people who bought this also…’?

Analyzing questions: the goal of Data Science degrees

There are two types of questions that you will tackle in interviews:

Conceptual questions: 

These questions relate to the main concepts in the field. While these questions appear simple, your answers reveal your breadth of knowledge as you answer them in detail. Thus, there is no way you can get past an interview without authentic understanding.

Technical questions: 

Even if you have exposure to this field or have previously worked with it, you would not know everything. The technical questions highlight your depth of experience and check your understanding of the nitty-gritty of the field.

Data Science & Analytics education: cracking the interview

A curriculum that is well-researched and covers different topics that will build your expertise: 

• Data Science Process
• The Interface between Computer Science and Statistics
• Statistical Techniques
• Regression Analysis
• Programming
• Data Modeling
• Data Visualization and Presentation
• Big Data Analytics
• Artificial Intelligence and Machine Learning

Here are top data science programs that can ensure that you get high-quality education in Data Science that employers would recognize and value:

• Advanced Data Science Certificate Program by Rotman School of Management (University of Toronto) 
• Data Science and Analytics for Business by Shiv Nadar University
• Master of Science Degree Programme in Data Science by IU International University of Applied Sciences

These high-end courses will help navigate the standard interview questions and train you to be a thought leader in this field. The high quality of education and the depth of technical knowledge means you will be ready to lead transformation in your organization. You can play a critical role in shaping how the company works with data with the correct input.

Frequently Asked Questions (FAQs)

• What is the future of Data Science?

The pandemic has tremendously accelerated the digital revolution. The way entrepreneur’s run an organisation has changed much more rapidly than before. Like the invention of the internet and social media, Data Science is here to stay. 

• Is doing Data Science worth it?

The world’s most prominent corporate houses are Data Science-driven companies. The list includes big names like Google, Amazon, Facebook, Alibaba, Jio, Airbnb, and more. Therefore, this is a big platform, and there is no shortage of jobs for those who hold a credible Post Graduate or M.Sc. degree. 

• How can I apply for the Data Science Course?

You can apply for the certificate courses using a Graduate degree in Science or Computer Science. Any other basic graduation with the choice of Mathematics in 10+2 also makes you eligible for these courses. For a Master’s in Data Science, a minimum of 1 year of work experience is required. You do not need knowledge of Python beforehand because you can learn that once you begin your training. To apply for any of the courses, get in touch with Jaro Education’s program experts. 

• How will I be evaluated during the Data Science Course?

These courses are learning outcome-based. The structure strikes a suitable balance between supervised and independent study. The evaluation will be through tests, performance, and participation in projects.

Conclusion

Interviews in the technical field are a combination of conceptual and applied questions. This testing of your knowledge is in addition to the other questions related to your background, experience, and soft skills. Unlike non-technical fields such as sales and marketing, where aptitude and presentation alone can determine hiring, knowledge of the subject is crucial in Data Science hiring. Taking a course that offers expertise is the best way to acquire this knowledge.