Quick interview tips for analytics interview – What are the benefits of doing company research before interview?, Here are some tips for preparing for an analytics interview, Brush up on the basics, Prepare for technical questions, Demonstrate your problem-solving skills, Highlight your communication skills, Be familiar with industry trends, Be confident and personable, What are guesstimates asked in analytics interview etc.
Analytics field is on the rise in last 1 decade or so because of digital revolution that led to creation of massive amount of data and hence comes the requirement of analytics professionals to crunch that data to deliver relevant insights to impact businesses.
Table of Contents
Number of Rounds in Typical Data Analyst Interview Process
Initially the resume gets shortlisted by HR and passed over to hiring manager. Hiring manager then shortlists candidates from the resumes provided to him. Once the shortlist happens by a hiring manager, HR schedules call with the candidate.
For qualifying as data analyst typically 4 round happens viz.
- Introductory round: First round is the exploratory call to find out if candidate is suitable for the job role or not. Questions are asked based on resume of candidate, technical skills are checked along with other soft skills like communication skills, teamwork and collaboration skills, grit, perseverance etc.
- Technical round: In this round candidates technical skills are put to check i.e. if he has the required skills in SQL/python, has hands on experience in visualisation tools like tableau, looker etc.
- Business round: In this round business acumen of the candidate is checked i.e. how he uses his technical skills to solve business problems,
- HR Interview: Once everything seems fine then in HR round candidates soft skills and other relevant skills are checked.
So, once the candidate clears all the round final offer is placed based on their salary expectation.
General data analyst interview questions
- Tell me about yourself
The reason why interviewer ask this question is to get general idea about the candidate and it helps interviewer to frame their next questions based on answer. Candidates can use this as opportunity to leave a good first impression on interviewer.
- What makes you the best candidate for the job?
This is another very commonly asked question in the interview to determine if candidate understands the job’s responsibilities, assess candidates confidence, see if they can deliver in the job role and can handle the challenges in the workplace.
- Tell me how you coped with a challenging data analysis project
This question is asked to check you problem solving skills using data and how you solved the problem at hand i.e. whether you took someones help, upskilled yourself to solved the problem, or was it too wasy for you while it was difficult for others, you used your out of the box or deep thinking to solve the problem etc.
- What type of data have you worked with?
There are different types of data numerical and text, plus different analytics techniques viz. descriptive, predictive, diagnostic and prescriptive with each being used for different purpose.
So, interviewer such questions to understand what kind of domain knowledge you have and what kind of datasets you have worked on, where does your expertise lies, will you be beneficial in giving additional responsibility in the current role etc.
What are the benefits of doing company research before interview?
Every smart person always does some research about the thing they are going to do for e.g. if you are going to buy a car then it’s better to do some research on what kind of cars are available in the market, which all major companies are selling cars in that segment you are interested in.
Different types of cars are sedan, suv (sport utility vehicle), luxury segment, hatchback etc.
Example 2: If you are going on a trip to some destination then enquiring which all famous places are there that you can visit, how to reach to those destinations whether you have to take cab, metro or go by walking etc. actually helps in making trip a success. And this also saves time as well as money.
Benefits of doing research:
Researching about the company you are going to give interview for is of immense help as:
- It shows to interviewer that you are really interested in the job,
- Shows you are proactive and
- Shows you are making effort to come into the company.
Hence, all the above points actually adds credit to your candidature for the vacant position.
What kind of research one should do is:
One should try to understand as much as possible about the company like:
- Mission and vision of company,
- Business model of the company,
- Know a bit about the industry in which company lies,
- How you can make impact in the company i.e. what kind of value you can add to the company using your analytical skills or using your other skills,
- Prepare for this in advance i.e. what you are going to say, how you are going to say and when you are going to say it in your interview. Plan it well.
- Research about their nearest competitors etc.
So, once you are done with researching about the company next steps is to brush up your skills and preparing for interview which we will discuss in next section.
Here are some tips for preparing for an analytics interview:
Step 1. Brush up on the basics:
First thing is to brush up the basics for interview. Make sure you have a solid understanding of:
- Basic statistical concepts,
- Data modelling techniques, and
- Data analysis tools.
Brushing up your skills or revising your notes/knowledge before exam is very good as that improves –
- Your understanding of the subject,
- Improves your ability to retain,
- Helps in recalling things during the exam or interview,
- Improves your performance and confidence,
- Reduces stress etc.
Now, the next question comes to you is what all to revise before your interview, so:
- Revise statistical concepts, probability theory like bayes theorem, mean, median, mode etc. why they are used and how to calculate them.
There is a lot of online literature available already or if you need help from us please let us know in comment section.
Step 2. Prepare for technical questions:
Expect to be asked technical questions on topics like:
- About your experience,
- About data analysis tools,
- About programming languages such as Python, R, SQL, or Excel,
- Practice coding exercises and be prepared to explain your methodology and thought process.
Make your resume very-very carefully as that is what helps in short listing you for interview and in interview also they will refer your resume to test your skills for the job.
Step 3. Demonstrate your problem-solving skills:
Analytics interviews often involve case studies or hypothetical problems that test your ability to apply your analytical skills to real-world situations. So,
- Practice solving sample problems and
- Be ready to articulate your reasoning and conclusions.
How you use your skills to solve real problems is very important, because each problem is unique and so just knowing tool or algorithm is not enough. But, knowing how to use those tools/skills to solve real problems is actually what matters.
Let us know if you need our help on this topic further.
Step 4. Highlight your communication skills:
Analytics is about translating complex data insights into actionable recommendations, so being able to communicate your findings in a clear and concise manner is crucial. Be prepared to –
- Discuss your experience with data visualization tools, and
- How you have presented data insights to non-technical stakeholders in the past.
Practice speaking or communicating your ideas well before the interview.
Step 5. Be familiar with industry trends:
Stay up-to-date with the latest developments and trends in the field of analytics, such as:
- Machine learning,
- Data privacy, and
- Data ethics.
This will demonstrate your passion for the field and your commitment to ongoing learning and professional development.
Step 6. Be confident and personable:
Finally, be confident in your abilities and show your personality during the interview. Remember that analytics is a collaborative field, so demonstrate that
- You are a team player and
- Can work well with others.
By collaborative it means you have to work with others to get the work done and so having skill to work with others to get the work done is very important.
Once you take care of above points your chances of cracking the interview will increase. Good luck with your analytics interview!
What are guesstimates asked in analytics interview?
Guesstimates refer to a type of estimation or approximation that is based on
- Reasoning, and
- Common sense.
rather than on precise data or statistical models.
Guesstimates are often used in business, finance, and other fields to quickly estimate the size or scope of a problem or opportunity.
Guesstimates typically involve making educated guesses based on limited information, such as:
- Market trends,
- Historical data, or anecdotal evidence.
Guesstimates are often used in situations where
- Precise data is not available or
- Where time is of the essence,
and they can be useful in guiding decision-making or prioritizing actions.
For example, a business might use guesstimates to estimate the potential revenue from a new product or service, based on the size of the target market and industry trends.
Similarly, a project manager might use guesstimates to estimate the time and cost required to complete a project, based on previous experience and knowledge of the industry.
While guesstimates can be useful in certain situations, they should be used with caution, as they are inherently less reliable than estimates based on precise data and statistical models.
It’s important to recognise the limitations of guesstimates and to validate them with additional research and data when possible.
Q1: Researching about the company you are going to give interview for is of immense help because:
Ans: Because it show that you are interested in job, is proactive and making serious effort to get selected.
Q2: Describe analytics in layman terms?
Q3: What is customer analytics?
Ans: Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics.
Other relevant links: