How do I prepare for a Data Science interview

Key takeaways:

• Today, the generation and application of information acquired through data is a crucial economic activity. Data science facilitates the power to extract information from a large volume of databases, making it simple to process the data to provide fruitful results. 

• The role of the Data Scientist has been proven to obtain real-time information in various public service fields, including health-related research, fraud detection, financial market analysis, environmental protection, energy exploration and more.   

• Data science interview questions can be intimidating due to the technical tests involved. Hence to ace the interview, learning how to prepare is important, increasing your chance of walking away with your job offer.

Data Science is one of the top career options for aspiring youngsters from technology backgrounds, thanks to the world going through an era of data explosion. According to a recent survey, the number of businesses hiring data scientists has increased from 30% to 60% within one year. Moreover, given the pace that we are moving towards digitalisation, the professional sure is here to stay.

While the demand for a data scientist is growing, data science interviews can be terrifying since it’s hard to navigate the competitive landscape. If you are in the same scenario, you have landed in the right place. Scroll on to discover more about the framework that will help you streamline your data science interview questions preparation through every step of your career journey. 

Steps in a data science hiring 

Are you feeling overwhelmed about how to begin your preparation journey for a data scientist interview? You are not alone! Organisations constantly seek ways to improve their hiring process to source and recruit talented data scientists. Let’s dive in to learn about the step-by-step process of data science hiring.

• Getting applications

When the company lists its job vacancy, it receives hundreds and thousands of applications. In such cases, recruiters will analyse the CV and portfolio of the candidates to sort out the passionate enthusiasts with strong academics and proper experience.

• Pre-screening 

Once the organisation decides the requirements of the job profile, it will plan a proper pre-screening test with basic questions about motivation and qualification. This simple assessment will reduce the application pool and enable them to understand whether the candidate can face highly demanding technical challenges.

• Technical assessment

The candidates who have cleared the pre-screening will be invited to participate in the technical test, which will have the basic operations regarding the role. In this process, transparency is inevitable since it will readily screen out candidates with minimum technical skills.

• HR interview

In most situations, the candidate will start their interview process by talking to the Human Resource Recruiter on the phone. Even though there will be basic questions, you should be prepared to outsmart yourself while explaining the ‘tell me about yourself, assuring them you will be a good fit for the company.

• Onsite interview

The onsite is the most challenging step before you achieve the job offer. It is more comprehensive than the former steps and typically combines 4 or 5 interviews in a single stage. The combination might vary based on the type of role you have applied for.

• Onboarding

After successfully completing all the hiring stages, you will be moved to the onboarding process, where the employers will explain your role, timelines, and requirements in detail. This is an opportunity for the candidates to learn about the company and the perfect time to address your concerns.

How to prepare for a data science interview?

Do you have a data science interview around the corner? It is easy to get nervous over the process because of the fear of being unable to answer the data science interview questions accurately. Nonetheless, every interview is a new learning experience. Here, we have compiled various factors that must be implemented before your interview to help you get into the recruitment pipeline. 

• Build compelling resume

Before you prepare for your data science interview questions, you must spend adequate time crafting the basic professional material – the resume and cover letter. Building a compelling resume is essential since they show the recruiters how you chose to represent you and your skills as a professional. 

Avoid typos and boasting about yourself with pages long since it will lead to rejection. Instead, ensure the resume is well-prepared in a definite matter, captivating the attention of employers with your skills and achievements. 

• Develop a portfolio

Recruiters looking to hire data scientists for their organisations prefer those with a great project portfolio. Despite the applicant’s educational background, they must showcase their performance and skill set in various technological projects. Hence while applying for the data science job, you need to get hands-on experience to land a top gig as a potential data scientist.

• Brush up on coding skills

The frequency of coding questions might vary from one organisation to another. Hence you should brush up on your coding skills, encompassed in subcategories of SQL, Data structure and algorithms, Modelling, and even statistical coding. 

It is because most data scientist recruiters require a person with a solid technical skill set who can work their organisation’s huge datasets, understating the complexity and solving real-world problems.

• Revisit basic concepts

Demonstrating your skill in any data scientist interview is challenging unless you are proficient in basic concepts of the field. Hence, if you are out of touch with the basics of data science, then it’s time to revive your knowledge of the fundamentals. The candidates need to familiarise themselves with datasets, coding algorithms, and popular case studies related to data science.    

• Prepare answers for commonly asked questions

No matter how hard you have prepared for the interview, you might always be curious about the structure of the interview and the type of question you will be asked. Hence, practising commonly asked questions will help you understand the issue’s scope and constraints. 

Moreover, data science interview questions are not only about getting the right answers. It is about your critical thinking and how you collaborate with others.      

• Understand the role and the company

Despite the interview stage you are in, learn more about the role you have applied for and the company. Research is the essential trend to know about the organisation in the industry and learn about competitors’ actions. 

If you have a greater idea of your role’s expectations and the company’s vision, it will be easy for you to prove what you can do for their development.

• Prepare some questions to ask the interviewer

And in the final part of your interview, employers might give you a chance to voice your questions. Remember, as an aspiring data scientist. You should always have some questions in hand to ask them as it indicates that you are truly interested in the position and company. 

You can also ask about your concerns or doubts since it will be the best time to clear them out. Some of the good questions you can ask your interviewer are – 

• How new is the role?
• Are there any previous instances of the company using results delivered by data scientists?

Type	Questions
Situational	Tell us one of the most challenging data science project you have worked on
Data Analysis	How should one treat outlier values?
Machine Learning	How do you avoid overfitting your model?

Top interview questions for data science

Data science is an interdisciplinary field that combines statistics, machine learning, computer science and other technologies to extract patterns and valuable insights. Here are some of the common interview questions for data science.

Python interview questions for data science

The ability to solve Python coding in data science is the best way to ace the interview. There we will lead you through the most commonly asked python-related questions for both fresher and experienced professionals.

Statistics interview questions for data science

The most important part of data science interview questions ranges from basics like central tendency to applying p-value in the project. Let us explore some statistical interview questions for a data science interview.

Tips to excel in the interview 

Interviewing in data science is a tricky part. Hence we have outlined some effective tips to help you make a great first impression. 

• Despite the interview stage, presenting yourself with a positive impression is the most critical part of the process. You may be an excellent grade-holder and proficient in skills, but it will not usually convince your employer to hire you. From arriving in smart business attire and maintaining body language to voicing the responses in the right mindset will significantly impact the employer’s decision.

• Even though you want to make yourself appealing, don’t extra-embellish your technical skills or experience. For instance, if you don’t have an SQL skillset beyond academics, be honest and upfront about it. Employers emphasise character, similar to your skills and experience with tools. 

• Go through the entire job description thoroughly, and know the expectations and take from the organisation. With a clear idea, you can nail the interview confidently by tailoring your responses to cater to your technical skills, soft skills, or critical thinking ability.

• If you have researched the company, prepare a set of genuine questions instead of asking generic ones for the sake of it.  Clarifying the questions and concerns like ‘what would a typical work of a data scientist look like in your firm’ at the end of the interview will be more appropriate and enable you to take your final decision for the role.

• It’s a good idea to come to the interview prepared. However, the mode doesn’t have to resemble a Q&A session about machine learning and case studies. Be engaged in the interview and make it sound like a conversation from the outset. A two-way conversation mode will be more effective and impress your recruiter while you contribute your thoughts. However, avoid interrupting your interviewer.

Conclusion 

The demand has increased for highly qualified professionals who understand the business and technological era in the data science industry. Acquiring an advanced data science certification is the key to remaining confident and competitive in the market and gaining a lucrative career. 
Enrol in the smart Master’s Program in Data Science offered by the Manipal Academy of Higher Education (MAHE) with Online Manipal to gain high-quality career-oriented education. Ultimately, the key aspects to achieving victory in the data science interview can be summed up by putting your efforts into being adequately prepared, which will give you the confidence to succeed.