HCL Technologies Data Scientist Interview Questions + Guide in 2024

HCL Technologies is a leading global IT services company known for its innovative approach to providing cutting-edge technology solutions. The company excels in transforming businesses with its expertise in technology and a deep understanding of the industry’s intricate dynamics.

As a Data Scientist at HCL Technologies, you will be expected to analyze raw data, design scalable prediction algorithms, and collaborate with engineering teams to bring analytical prototypes to production. The ideal candidate should exhibit strong collaborative skills and the ability to extract valuable insights from complex data sets.

In this guide, we will walk you through the interview process, typical HCL data scientist interview questions, and valuable tips to help you succeed. Let’s get started!

Recruiter/Hiring Manager Call Screening

If your CV is shortlisted, a recruiter from HCL Technologies will contact you for an initial screening. This conversation usually involves verifying your experience, skills, and interest in the role. Expect to answer behavioral questions and provide more details about your background and previous projects.

The recruiter call typically lasts about 30 minutes and might also include some technical questions based on the skill set required for the position.

Technical Virtual Interview

Clearing the recruiter screening round will lead to a technical interview conducted virtually via video conference. This stage often includes questions on data science projects you’ve worked on, as well as ML algorithms, coding in Python, and statistical methods.

Some of the typical questions you might encounter include:

• List all the machine learning algorithms you know.
• What are the assumptions for linear regression, and how do you address them if they fail?
• Explain PCA and its importance.
• Detail your approach when two independent variables are highly correlated.
• What are AIC and BIC, and why are they important?

The technical interview assesses your understanding of data science principles, machine learning algorithms, and problem-solving approaches.

Onsite Interview Rounds

If you pass the technical virtual interview, you’ll advance to the on-site interview loop. The on-site interview generally includes multiple rounds where various aspects of your technical abilities and fit for the team are evaluated. Questions will dive deeper into your previous projects and explore your coding capabilities, machine learning knowledge, and domain expertise.

Expect a mix of technical discussions, real-time problem-solving scenarios, and behavioral questions to help you understand your soft skills and how you work in a team.

Sometimes, you may also be given a case study to prepare beforehand and discuss during one of the on-site rounds. Different team members might conduct each interview session, including a team lead, data scientists, and a hiring manager.

Typically, interviews at HCL Technologies vary by role and team, but commonly data scientist interviews follow a fairly standardized process across these question topics.

1. Write a SQL query to select the 2nd highest salary in the engineering department.

Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

2. Create a function to find the maximum number in a list of integers.

Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return None.

3. Create a function convert_to_bst to convert a sorted list into a balanced binary tree.

Given a sorted list, create a function convert_to_bst that converts the list into a balanced binary tree. The output binary tree should be balanced, meaning the height difference between the left and right subtree of all the nodes should be at most one.

4. Write a function to simulate drawing balls from a jar.

Write a function to simulate drawing balls from a jar. The colors of the balls are stored in a list named jar, with corresponding counts of the balls stored in the same index in a list called n_balls.

5. Create a function can_shift to determine if one string can be shifted to become another.

Given two strings A and B, write a function can_shift to return whether or not A can be shifted some number of places to get B.

6. How much should we budget for a $5 coupon initiative in a ride-sharing app?

A ride-sharing app has a probability (p) of dispensing a $5 coupon to a rider and services (N) riders. Calculate the total budget needed for the coupon initiative.

7. What is the probability of both or only one rider getting a coupon?

A driver using the app picks up two passengers. Determine the probability of both riders getting the coupon and the probability that only one will get it.

8. What is a confidence interval for a statistic, and why is it useful?

Explain what a confidence interval is, why it is useful to know the confidence interval for a statistic, and how to calculate it.

9. What is the probability that item X would be found on Amazon’s website?

Amazon has a warehouse system where items are located at different distribution centers. Given the probabilities that item X is available at warehouse A (0.6) and warehouse B (0.8), calculate the probability that item X would be found on Amazon’s website.

10. Is a coin that comes up tails 8 times out of 10 fair?

You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if this coin is fair.

11. What are time series models and why are they needed?

Describe what time series models are and explain why they are necessary when simpler regression models are available.

12. How would you explain linear regression to a child, a first-year college student, and a seasoned mathematician?

Explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician. Tailor your explanations to each audience’s understanding level.

13. What happens when you run logistic regression on perfectly linearly separable data?

Given a dataset of perfectly linearly separable data, describe the outcome of running logistic regression on it.

14. How would you evaluate and deploy a decision tree model for predicting loan repayment?

As a data scientist at a bank, you need to build a decision tree model to predict if a borrower will repay a personal loan. Evaluate if a decision tree is the correct model, and describe how you would assess its performance before and after deployment.

15. How would you justify using a neural network model to non-technical stakeholders?

Your manager asks you to build a neural network model to solve a business problem. Explain how you would justify the complexity of the model and its predictions to non-technical stakeholders.

16. How does random forest generate the forest, and why use it over logistic regression?

Describe the process by which a random forest generates its forest. Additionally, explain why one might choose random forest over logistic regression for certain problems.

17. What are the drawbacks of the given data organization, and how would you reformat it for better analysis?

Assume you have data on student test scores in two different layouts. Identify the drawbacks of these layouts and suggest formatting changes to make the data more useful for analysis. Additionally, describe common problems seen in “messy” datasets.

18. How would you locate a mouse in a 4x4 grid using the fewest scans?

You have a 4x4 grid with a mouse trapped in one of the cells. You can scan subsets of cells to know if the mouse is within that subset. Describe a strategy to find the mouse using the fewest number of scans.

19. How would you select Dashers for Doordash deliveries in NYC and Charlotte?

Doordash is launching delivery services in NYC and Charlotte and needs a process for selecting dashers. Describe how you would decide which dashers to select and whether the criteria would be the same for both cities.

20. What factors could bias Jetco’s boarding time study, and what would you investigate?

According to a study, Jetco, a new airline, has the fastest average boarding times. Identify potential biases in this result and describe what factors you would investigate.

21. How would you design an A/B test to evaluate a pricing increase for a B2B SAAS company?

A B2B SAAS company wants to test different subscription pricing levels. Design a two-week A/B test to evaluate a pricing increase and determine if it is a good business decision.

Here are some quick tips to ace your interview at HCL Technologies:

1. Brush Up on Core Concepts: Review key concepts in statistics, machine learning, and data science, as well as any specific tools or libraries you’ve mentioned in your resume.
2. Prepare for Projects Discussion: Be ready to discuss your previous projects in detail, including the objectives, methodologies, algorithms used, and outcomes. Understanding the practical application of your skills is crucial.
3. Understand Company-Specific Needs: HCL Technologies often tailors questions to the specific skills required for their projects. Reviewing the job description carefully can give you insight into what areas to focus on.

What is the average salary for a Data Scientist at HCL Technologies?

According to Glassdoor, the base pay for a data scientist position at HCL Technologies ranges from ₹6L to ₹16.3L per year, with the average pay of ₹2L per year.

What kind of questions are asked in the technical rounds?

You can expect questions on various topics like ML algorithms, differences between techniques like SVM and Naive Bayes, PCA, linear regression assumptions, AIC and BIC, confusion matrix in medical applications, precision and recall. Coding questions, such as creating data frames from dictionaries in Python, are also common.

What is the general feedback on the interview experience?

Feedback is mixed. While some candidates report a positive experience with interviewers, others have faced a lack of clear communication post-interview. Multiple candidates have noted that the interviewers seemed to lack detailed knowledge of Data Science and Machine Learning.

If you want more insights about the company, check out our main HCL Technologies Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about HCL Technologies’ interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit. We equip you with the knowledge, confidence, and strategic guidance to tackle every HCL Technologies Data Scientist interview question and challenge.

For better preparation, you can check out all our company interview guides.

Good luck with your interview!