Data Science interview questions

DevSkiller’s team produces Data Science interview questions for assisting recruiters aiming to hire Data scientists. Our tests are designed to ensure you find the perfect candidate through our unique range of challenges and questions.

We implement RealLifeTesting™ into our Data Science interview questions. This methodology is designed to simulate real-world scenarios and present candidates with realistic problems to solve. RealLifeTesting™ is a pioneering method for developer recruitment. Let us help you find your next Data scientist today, using our range of Data Science interview questions.

Python
MIDDLE
Tested skills
Duration
72 minutes max.
Evaluation
Automatic
Test overview

Choice questions

assessing knowledge of Machine Learning, Reinforcement learning

Programming task - Level: Medium

Python | PyTorch | Reinforcement Learning | Deep Q-Network - Complete the implementation of the DQN algorithm.

Python
JUNIOR
Tested skills
Duration
65 minutes max.
Evaluation
Automatic
Test overview

Choice questions

assessing knowledge of Python

Programming task - Level: Easy

Python | PySpark | ML Logs Transformer - Complete the implementation of the logs transformation pipeline.

Scala
JUNIOR
Tested skills
Duration
66 minutes max.
Evaluation
Automatic
Test overview

Choice questions

assessing knowledge of Scala

Programming task - Level: Easy

Scala | Spark | ML Logs Transformer - Complete the implementation of the logs' transformation pipeline.

Data Science
JUNIOR
Tested skills
Duration
45 minutes max.
Evaluation
Automatic
Test overview

Task - Level: Easy

SQL | Stamps catalogue | The three highest prices - Select three stamps (price and name) with the highest price.

Programming task - Level: Easy

Python | Pandas | HTML table parser - Implement a function to convert HTML table into a CSV-format file.

Python
JUNIOR
Tested skills
Duration
63 minutes max.
Evaluation
Automatic
Test overview

Choice questions

assessing knowledge of Machine Learning, PyTorch

Programming task - Level: Easy

Python | PyTorch, Computer Vision | Model Builder - Complete the implementation of a model training pipeline.

Python
MIDDLE
Tested skills
Duration
120 minutes max.
Evaluation
Automatic
Test overview

Choice questions

assessing knowledge of Python

Programming task - Level: Medium

Python | Vehicle sales report - Implement an application to create reports based on the vehicle sales data warehouse.

Python
MIDDLE
Tested skills
Duration
96 minutes max.
Evaluation
Automatic
Test overview

Choice questions

assessing knowledge of Python

Programming task - Level: Medium

Python | Pandas | A food delivery startup - Transform a database of orders by reducing its dimensionality and creating an additional analytical table.

Python
JUNIOR
Tested skills
Duration
45 minutes max.
Evaluation
Automatic
Test overview

Choice questions

assessing knowledge of Python

Programming task - Level: Easy

Python | Client Base Creator - Implement the application to retrieve customer's contact data from the chat messages.

Python
MIDDLE
Tested skills
Duration
70 minutes max.
Evaluation
Automatic
Test overview

Choice questions

assessing knowledge of Machine Learning, Python

Programming task - Level: Medium

Python | DNA Analyzer | Create and clean DNA strands - Implement 2 methods in Python that create and clean DNA strands.

Python
JUNIOR
Tested skills
Duration
49 minutes max.
Evaluation
Automatic
Test overview

Choice questions

assessing knowledge of Machine Learning

Programming task - Level: Easy

Python | DNA Analyzer - Implement a method in Python that generates DNA statistical report.

NumPy
MIDDLE
Tested skills
Duration
80 minutes max.
Evaluation
Automatic
Test overview

Choice questions

assessing knowledge of *SQL

Programming task - Level: Medium

Python | NumPy | Aircraft measurement data processing - Complete data processing application that aggregates and compresses data streams using NumPy, Python and Data Analysis.

Recommended roles for Data Science interview questions

  • Junior data scientist
  • Middle data scientist
  • Senior data scientist
  • Machine learning engineer
  • Machine learning scientist
  • Application architect
  • Enterprise architect
  • Data architect
  • Infrastructure architect
  • Data engineer
  • Business intelligence developer
  • Data analyst

How our Data Science interview questions work

The driving force behind DevSkiller Data Science interview questions is the RealLifeTesting™ methodology. It powers our unique approach to developer testing. RealLifeTesting™ functions around the principle that to get the best out of a developer, you need to present them with challenges similar to their everyday work. We use RealLifeTesting™ to simulate a developer’s work environment and then set them realistic challenges to overcome. In this way, we are able to offer you a thorough overview of a developer candidate’s strengths and weaknesses from the initial screen stage of recruitment.

Say goodbye to endless hours of monotonous, in-house testing. At Devskiller, we can offer you a clear understanding of your applicants’ knowledge, coding ability, critical thinking, and time-management skills. Our testing method works remotely and efficiently, saving you hours of time and effort during the recruitment process.

Key features

  • DevSkiller Data Science interview questions provide a holistic view of an applicant’s coding skills, not just their academic knowledge.
  • Remote testing that will save you time and money.
  • The RealLifeTesting™ methodology offers a greater user experience where candidates can use their own IDE, clone to GIT, run unit tests, and access Stack Overflow/GitHub/Google for research.
  • We provide test assurance with strict anti-plagiarism tools enforced
  • Observe individual tests in real-time
  • Automated results that non-technical professionals can understand
  • Tests available for all levels of experience

Skills covered in our Data Science interview questions

  • Data engineering
  • data science
  • ETL
  • PySpark
  • Python
  • Scala
  • Data analysis
  • HSQL
  • DB
  • MySQL
  • Pandas
  • SQL
  • Computer Vision
  • Machine Learning
  • PyTorch
  • Data Analysis with Python
  • SQLite
  • Dimensional Modelling
  • Python 3.x
  • Data Structures
  • NumPy
  • Android
  • data extraction
  • OCR
  • PDF processing

What to look for in a Data scientist

Data Science is a way of making decisions and predictions through predictive causal analytics, as well as prescriptive analytics, and machine learning. A data scientist’s responsibilities include looking at exploratory data analysis, machine learning and advanced algorithms, and data product engineering.

DevSkiller’s Data Science interview questions can help you to whittle down the candidates who are the best critical thinkers. Data scientists need to possess the ability to objectively analyze the data presented to them before forming an opinion. The Data Science candidate you choose to recruit will need to show their proficiency in coding and be comfortable with a variety of programming tasks.

It will be preferable if your Data Science candidate is privy to various programming languages, but mainly Python and R. They will be analyzing data on a daily basis so they will need to demonstrate their proficiency in both mathematics and statistics.

Finally, if your candidate can demonstrate ability in machine learning, deep learning, or AI, then this will all work in their favor. Advances in these areas are happening rapidly so it will be advantageous if your Data scientist is up to date with advances in the industry, in order to remain ahead of the curve.

Build your own custom Data Science test

Some of our past clients have created their own interview questions, tailored to their business’s needs. Perhaps you would like to do the same?

Our range of Data Science coding tests can be altered to your needs. Opt for a test duration that suits you better, choose which questions are the most relevant, and even alter the difficulty level of each test.

Remote testing means you can conveniently assess candidates from all corners of the globe. Did we mention that you can even observe tests in real-time? That’s right, you can choose to observe how well each candidate is performing even while they are taking their test!

Still unsure about our Data Science interview questions?

If you’re still not completely convinced by our Data Science coding tests, check out what others are saying about us:

Patrycja Kiljańska – Talent acquisition specialist at Spartez

“We’ve replaced a high-maintenance in-house solution with DevSkiller. Our process looks the same, however, the product gives us better performance. The results are also way easier to assess.

Michael Gerwig – Engineering manager at Ada Health

“DevSkiller helped us to save precious on-site time for applicants that are already likely to be a fit. We’re saving 3 hours per candidate – that was the time we spent with applicants on a technical task before.”

Frequently asked questions

What is RealLifeTestingTM?

The RealLifeTestingTM methodology is behind all of DevSkiller’s Data Science interview questions and coding tests. We don’t use traditional game-like quizzes or algorithmic puzzles that don’t accurately assess how well a developer will actually perform in the role. Instead, we use RealLifeTestingTM to recreate a Data scientist’s everyday work environment and assess them using challenges that reflect those they usually encounter. RealLifeTestingTM provides us and our clients with a holistic view of each applicant’s entire skillset. When the challenges mirror real issues, then the responses reflect how well that candidate will cope.

Our Data Science interview questions expect candidates to possess the critical thinking needed to determine the best method for resolving problems they may encounter. Results are automatically generated and are assessed on the candidate’s decision-making and problem-solving skills.

How do candidates undertake Data Science interview questions?

One of the main advantages of DevSkiller testing is that our Data Science interview questions are easily accessible online. Recruiters can send test invites to their candidates and then the tests themselves can be taken from anywhere they choose. This is a great time-saver, as your Data Science candidates can send their tests back as soon as they’ve finished, no more waiting around for in-house tests to be completed.

Even better is that our tests are assessed automatically as well. Once the candidate has finished, our system gets to work on their answers and then produces an automated, non-technical report detailing how they performed. Meaning all the recruiter has to do is send out the invites and await the results.

What do candidates think of DevSkiller tests?

The feedback we get from developer candidates is that they love how closely our tests resemble the real work they do. Developers often grow tired of developer testing involving algorithmic tests and tasks reciting coding patterns, as this method doesn’t allow them to really show off their skills. Once they realize our tests aren’t following the same pattern, they relish being given the chance to perform.

Our tests allow candidates to work on our state of the art in-browser IDE, or to use their own, and they can run unit tests, much like they would in their real work. Developers are awarded a chance to prove their actual software development skills and to use normal coding tools and conventions that reflect their work. It is refreshing for candidates to be able to prove their skills in a fair setting.