Interview Questions

Data Scientist Interview Questions

A data scientist is a professional who is responsible for extracting meaning from data. Data scientists use their skills in statistics, computer science, and mathematics to make sense of data. They use their findings to help organizations make better decisions.Data scientists typically have a strong background in one or more of the following: statistics, computer science, and mathematics. They also have strong skills in communication and visualization.

Questions

1,000

Stay in the loop!

No spam. Just the latest releases and tips, interesting articles, and exclusive interviews in your inbox every week.

What is a Data Scientist?

A data scientist is a professional who is responsible for extracting meaning from data. Data scientists use their skills in statistics, computer science, and mathematics to make sense of data. They use their findings to help organizations make better decisions.Data scientists typically have a strong background in one or more of the following: statistics, computer science, and mathematics. They also have strong skills in communication and visualization.

Image courtesy of Laura Davidson via Unsplash

“Acquiring the right talent is the most important key to growth. Hiring was - and still is - the most important thing we do.”

— Marc Benioff, Salesforce founder

How does a Data Scientist fit into your organization?

Data scientists are in high demand these days as organizations seek to make better use of the data they have at their disposal. But what exactly is a data scientist and what role do they play in an organization?A data scientist is someone who is skilled at extracting insights from data. They use their knowledge of statistics, machine learning, and programming to find patterns and relationships in data that can be used to make predictions or recommendations.Data scientists typically work in one of two roles:1. They may work on a team that is responsible for developing and deploying predictive models. In this role, they work closely with software engineers and other data scientists to build and test models, and then deploy them into production.2. They may also work as part of a business team, providing insights and recommendations based on data analysis. In this role, they work closely with business analysts and decision makers to understand the business problem and then use their data skills to find the best solution.Regardless of which role they play, data scientists must be able to effectively communicate their findings to non-technical audiences. They also need to be able to work well in teams, as most data science projects involve collaboration with others.If you're thinking about adding a data scientist to your team, it's important to first consider what role they will play and what skills they will need to be successful. Only then can you determine whether or not a data scientist is a good fit for your organization.

What are the roles and responsibilities for a Data Scientist?

What is a Data Scientist? Data scientists are responsible for extracting meaning from data to help organizations make better decisions. Data scientists typically have a strong background in mathematics, statistics, and computer science, and they use their skills to solve complex business problems.What are the responsibilities of a data scientist? A data scientist’s responsibilities may include Cleaning and organizing dataPerforming statistical analysisBuilding predictive modelsCommunicating results to stakeholdersDeploying models into productionMonitoring model performanceWhat skills do you need to be a data scientist? In order to be successful in this role, you will need strong technical skills, including Programming languages (R, Python, SQL, etc.)Statistical analysisMachine learningData visualizationYou will also need to be able to effectively communicate your findings to non-technical stakeholders.

What are some key skills for a Data Scientist?

Some of the important skills for a data scientist include: - Machine learning: In order to make predictions or recommendations, data scientists need to be able to understand and work with data using machine learning algorithms. Programming: Data scientists need to be able to code in order to wrangle data, build models and algorithms, and automate processes. Popular programming languages for data science include Python, R, and SQL. Data visualization: Data scientists need to be able to effectively communicate their findings to others through data visualizations. This skill is important in order to make complex data sets accessible to non -technical audiences. Business acumen: Data scientists need to be able to understand the business context in which they are working in order to make recommendations that are aligned with business objectives. Domain expertise: Data scientists need to have a deep understanding of the domain they are working in, whether it’s healthcare, retail, finance, etc. This understanding is necessary in order to make accurate predictions and recommendations.

Top 25 interview questions for a Data Scientist

What is the biggest data set that you processed, and how did you process it, what were the results? What does a data scientist need the most? Does a Data Scientist need to be better at statistics than a software engineer and better at software engineering than a statistician? How do you handle missing data? What imputation techniques do you recommend? How would you come up with a solution to identify plagiarism? What is the curse of big data? What do you think makes a good data scientist? What will you say the “best practices” in data science. What are your top 5 predictions for the next 20 years? What/when is the latest data mining book / article you read? What are your favorite data science websites? Who do you admire most in the data science community, and why? Which company do you admire most? In your opinion, what is data science? Machine learning? Data mining? What’s the best interview question anyone has ever asked you? How to Think Like a Data Scientist? What in your career are you most proud of so far? What publications, websites, blogs, conferences and/or books do you read/attend that are helpful to your work? What are the biggest areas of opportunity / questions you would like to tackle? What are your favorite data science tools? What are your favorite data science libraries or frameworks? When someone asks you “what does a data scientist do all day long?,” how do you respond? If you were to start again, what would you do differently as a data scientist? What are your favorite use cases for predictive modeling? How do you explain your findings to non-technical people? Do you think that Data Science is more about art or science? What will be the hottest areas of machine learning in the next 5 years? Describe a time when you had to analyze complex data. What is the most difficult part of being a data scientist? Tell me about a time when you had to use statistics in your work. Tell me about a time when you had to use machine learning in your work. Tell me about a time when you had to use data mining in your work. Tell me about a time when you had to analyze complex data sets. What is your experience with big data tools such as Hadoop and MapReduce? Tell me about a time when you had to use predictive modeling in your work

Top 25 technical interview questions for a Data Scientist

What is the curse of big data? What do you think makes a good data scientist? What will you say the “best practices” in data science. What are your top 5 predictions for the next 20 years? What/when is the latest data mining book / article you read? What are your favorite data science websites? Who do you admire most in the data science community, and why? Which company do you admire most? In your opinion, what is data science? Machine learning? Data mining? What’s the best interview question anyone has ever asked you? How to Think Like a Data Scientist? What in your career are you most proud of so far? What publications, websites, blogs, conferences and/or books do you read/attend that are helpful to your work? What are the biggest areas of opportunity / questions you would like to tackle? What are the biggest myths about data science? What have you done outside of work to become a better data scientist? What one piece of advice would you give to someone who wants to become a data scientist? If you were to start over again, what would you do differently? In your opinion, what is “big data”? What are the three most important skills for a data scientist? What are some of the ethical considerations in data science? What are some of the biggest challenges in data science? What is the most exciting thing about data science? What are your thoughts on the current state of data science? Where do you see data science headed in the future?

Top 25 behavioral interview questions for a Data Scientist

How do you handle missing data when developing predictive models? What are some of the most common issues you face when working with data? How do you go about finding patterns in data? What is your approach to dealing with outliers in data? What are some of the techniques you use to improve the accuracy of your predictions? What is your experience with Time Series Analysis? How do you deal with imbalanced data when developing predictive models? What is your experience with Survival Analysis? What is your experience with Dimensionality Reduction techniques? Tell me about a time when you had to deal with a difficult data set. Tell me about a time when you had to use creative methods to achieve your goals. Tell me about a time when you had to use advanced statistical methods to analyze data. Tell me about a time when you had to deal with a complex data set. Tell me about a time when you had to use machine learning algorithms to build a predictive model. What is your experience with text data? What is your experience with image data? What is your experience with audio data? What is your experience with video data? What is your experience working with big data? What is your experience working with streaming data? What is your experience working with unstructured data? Tell me about a time when you had to work with messy or incomplete data. Tell me about a time when you had to wrangle data to get it into a usable format. Tell me about a time when you had to perform exploratory data analysis. Tell me about a time when you had to solve a difficult problem using data science techniques.

Conclusion - Data Scientist

These are just a few of the many questions that you could be asked as a data scientist. However, these questions should give you a good idea of the types of skills and knowledge that employers are looking for in a data scientist. If you can answer these questions confidently, you will likely be a strong candidate for any data science position.

THE KEYSTONE OF EFFECTIVE INTERVIEWING IS HAVING GREAT INTERVIEW QUESTIONS

Browse Interview Questions by Role

Get Our List of Top 67 PROVEN Interview Questions for FREE

Enter your email and get instant access to our best interview questions -- absolutely FREE!

Recruiters love Hume

I was conducting around 20 video interviews per week and keeping track of every call was beginning to become basically impossible. Started using Hume and it increased the quality of the interviews almost instantly. Automatic transcriptions, Q&A analysis and sharing the interviews with colleagues were killer features!

Ismail Pelaseyed

CEO, Mersenne

How Hume Works

How does Hume work?

Hume Joins Your Interviews

Hume joins your interviews and automatically captures all candidate interactions across Zoom, Google Meet or Microsoft Teams (coming soon)

Create & Share Highlight Reels And Automated Summaries

Teams can instantly create and share interview highlight reels and get automated interview summaries and question extractions, decreasing #interviews per hire and speeding up time to hire

Hiring Decisions Based On Evidence, Not Gut Feelings Or Recall

With your interviews unlocked, you bring evidence into every hiring decision, drive efficiency and collaboration across hiring teams, and give insight into your organization’s hiring practices

Here's Why Recruiters & Talent Teams Use Hume

Hume gives me a video library of candidates that I can easily share with my team for faster, more reliable hiring!

Diane O'Brien

Executive Recruiter, Kaplan

You’re A Few Steps Away from Drastically Improving Your Hiring Speed And Saving 100s of Hours of Admin Time

You don't build a business - you build people - and then people build the business.

Product
Overview
Features

Integrations

FAQ

Pricing
Resources

eBooks

Help centre

Webinars

Interview Intelligence

Interview Templates

New
Social
Twitter
LinkedIn

Hume.

© 2022 Hume Technology AB. All rights reserved.