Data Science Interview Preparation: 10 Tips to Succeed

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A data scientist works with a sea of data to develop hypotheses and draw conclusions. This can be structured, unstructured or semi-structured data. Data wranglers refer to those who use different types of tools to analyse trends and patterns. The other roles include analytics, collaboration, management and strategy or design. These tasks are usually assigned by the Chief Data Officer, Senior Data Scientist and Head of Data Science. 

As per AIM research, there were 137,879 data science jobs in India in June 2021. There was a 47.1% increase in open job requirements compared to June 2020. The country also contributed to 9.4% of the total global analytics job openings, representing a rise from 7.2% in January 2020. If you wish to apply for a job in the lucrative and growing data science field, the first step is to prepare yourself. 

GeekLurn’s comprehensive Data Science Architect Program offers a 24-month course that is divided across 6 months of live interactive classes and 18 months of sponsored project work at authorised research centres. It includes tips and tricks to prepare for technical interviews and gain career growth hacks with valuable insights from industry experts under 1-on-1 career mentorship. This helps aspirants become fully job-ready. Here are some tips for data science interview preparation. 

Table of Contents

1. Brush Up Basic Concepts 

This includes statistics, probability, dimensionality reduction, hypothesis testing and descriptive and Bayesian statistics. Make sure to revise coding and programming languages, product sense, business application and data modeling techniques. This way you will be able to discuss how the knowledge of all these may add value to the company.

2. Research the Role 

Data science is an umbrella term that accommodates a wide range of profiles. 

Data EngineerData Science Project Manager
Data AnalystML Engineer
StatisticianBusiness Analyst

It’s important to have a clear understanding of the job description before turning up for the interview. This can put you at ease and showcase your interpersonal skills accordingly. It may also help you predict the questions and make sure your skills match the role. 

3. Prepare for Multiple Interviews 

If you are looking for how to prepare for data science interview, consider learning about each round in detail. The screening process will usually consist of online tests, phone interview and technical interview, followed by an HR interview. You may discuss various topics at different rounds like career plans, salary expectations, analytical skills and general data science knowledge. Prepare for all of them before heading out. 

4. Understand the Company 

You must know the business of the company well. Check the company’s website to know what it is working on, what is their mission and what are their future goals. Knowing the industry can help you use the right jargon to sound well-informed. Also, knowing more about the company will help you decide if you have the required foundation and expertise to join the team. You may also visit their social media pages and check out review sites to read reviews of customers and employees. This will give you insight into the work culture, values, systems and methods. It helps in crafting your answers and increases your chances of being selected for the job. 

5. Know the Requirements 

Some employers look for experts with hard skills, which allow people to hit the ground running. Others may be looking for freshers, who are ready to be trained as per their software requirements. Make sure to read the eligibility and requirements. This can help you identify whether you fit well into the role and get an idea of the kind of work expected from you. You can also tweak some of the data science interview preparation answers accordingly. 

6. Prepare to be Tested 

The interview board members might ask you to demonstrate a few skills. The most common ones are statistical analysis, programming, working with data, visualisation and modeling. Make sure these are at your fingertips to give an impression that you are adept at working with data. A good understanding of linear and logistic regression can help too. 

7. Be Honest About Your Experience 

Confidence and honesty can go a long way during interviews. You should remain upfront about the skills (both hard and soft) you possess and those that you don’t. Do not pretend to know it all, since dishonesty does not help in the long run. You will be surprised at how recruiters appreciate honest responses, since integrity and dedication are attributes most companies look for. They may be willing to teach you how to use tools and software and may consider you a good fit for their data science team and the company in general. 

8. Mock Interviews 

While pursuing the program at GeekLurn, mentors will help you practise for interviews. They can guide you about how to prepare for data science interviews. Going through mock interviews tends to boost your confidence. One may also learn useful tricks and get constructive and tailored feedback to ace the job interview.

9. Ask Questions 

Interviewers expect questions from candidates too. It shows that you are thinking about the given task, eager to understand assignments and meet your objectives. You may ask a few questions at the end of the interview. This conveys that you have listened well and are able to retain information. Some of the questions you may ask are: What would a typical workday at this office look like? What are your expectations from me? What are the company’s growth plans for employees?

10. Discuss Salary 

An entry-level data scientist with less than one year of experience may earn ₹5,00,000 per annum. Those with 1 to 4 years of experience can expect over ₹6,00,000 per annum. Research well and have an idea of your expectations. Make sure you do not feel awkward or uncomfortable by practising your answer beforehand. Talk about the responsibilities that come with a certain role and the expertise you will bring to the table. This will help both parties come to an appropriate salary. 

A data science interview is not a cakewalk. But neither is it rocket science. If you have completed a good course and remember some of these tips, you can hope to do well in the interview. Finally, dressing well and being courteous will always stand you in good stead.

Neel is a Product Manager with an interest in Data Science, Machine Learning, Cloud Computing, DevOps, and Blockchain with expertise in Python, R, Java, Power BI and Data analytics.

Neel Neeraj

Neel is a Product Manager with an interest in Data Science, Machine Learning, Cloud Computing, DevOps, and Blockchain with expertise in Python, R, Java, Power BI and Data analytics.
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