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.
assessing knowledge of Python 3.x, Logical thinking, Sequence, Soft Skills
Python | NumPy | Graph Convolutional Networks - Implement a simple Graph Convolution Network.
assessing knowledge of Python 3.x
assessing knowledge of Python 3.x
Python | Drug Analyzer - You are a member of a biotechnology programming team that is responsible for creating a system for lab technicians, which will assist them with drug analysis. Your goal is to create the application that will let them input their findings into the system, provide a meaningful analysis and verify the correctness of the data that they have sent.
assessing knowledge of Big Data, PySpark, Python
assessing knowledge of SQL
Python | PySpark | Fleet management corporation - Detect speeding events and verify correctness of an existing predictor.
assessing knowledge of Python, Spark
Python | PySpark | Customer Preference Model - Implement a Data Engineering application for preprocessing marketing data.
assessing knowledge of Keras, Machine Learning, Python
Python | NLP, Keras | Sentiment analysis of customer reviews - Perform a sentiment analysis and tagging of movie and airline customer reviews, using a multi-output neural network model.
assessing knowledge of Machine Learning, Reinforcement learning
Python | PyTorch | Reinforcement Learning | Deep Q-Network - Complete the implementation of the DQN algorithm.
assessing knowledge of Python
Python | PySpark | ML Logs Transformer - Complete the implementation of the logs transformation pipeline.
assessing knowledge of Scala
Scala | Spark | ML Logs Transformer - Complete the implementation of the logs' transformation pipeline.
SQL | Stamps catalogue | The three highest prices - Select three stamps (price and name) with the highest price.
Python | Pandas | HTML table parser - Implement a function to convert HTML table into a CSV-format file.
assessing knowledge of Python
Python | Pandas | HTML table parser - Implement a function to convert HTML table into a CSV-format file.
assessing knowledge of Machine Learning, PyTorch
Python | PyTorch, Computer Vision | Model Builder - Complete the implementation of a model training pipeline.
assessing knowledge of Python
Python | Vehicle sales report - Implement an application to create reports based on the vehicle sales data warehouse.
assessing knowledge of Python
Python | Pandas | A food delivery startup - Transform a database of orders by reducing its dimensionality and creating an additional analytical table.
assessing knowledge of Python
Python | Client Base Creator - Implement the application to retrieve customer's contact data from the chat messages.
assessing knowledge of Machine Learning, Python
Python | DNA Analyzer | Create and clean DNA strands - Implement 2 methods in Python that create and clean DNA strands.
assessing knowledge of Machine Learning
Python | DNA Analyzer - Implement a method in Python that generates DNA statistical report.
assessing knowledge of *SQL
Python | NumPy | Aircraft measurement data processing - Complete data processing application that aggregates and compresses data streams using NumPy, Python and Data Analysis.
assessing knowledge of SQL
Python | DNA Analyzer - Implement a method in Python that generates DNA statistical report.
assessing knowledge of Python
Python | NumPy | Aircraft measurement data processing - Complete data processing application that aggregates and compresses data streams using NumPy, Python and Data Analysis.
assessing knowledge of Machine Learning, Python
Python | DNA Analyzer | Create and clean DNA strands - Implement 2 methods in Python that create and clean DNA strands.
assessing knowledge of Python
Python | DNA Analyzer - Implement a method in Python that generates DNA statistical report.
assessing knowledge of Machine Learning, Python
Python Data Extraction, Processing - Complete and update the code for the program that extracts processes PDF files and converts them to a specific format for display/output.
assessing knowledge of Machine Learning, Android
Android | Social Network login - Implement missing sections of LoginActivity and MainActivity, LoginManager and CredentialsStorage.
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.
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.
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!
To improve candidate experience during our Python online tests, Devskiller has implemented a built-in Pycharm IDE directly into the browser. Our already warmed up, ready to use Pycharm IDE will reduce time during testing. This will increase the user experience for your candidates and help to reduce candidate drop-off during the hiring process.
Candidates no longer have to clone the code, wait for the dependencies to install or indexes to build. They can literally start coding as soon as they open the test invitation. This unique feature is just one of the innovations setting DevSkiller TalentScore apart from the competition when it comes to developer screening.
If you’re still not completely convinced by our Data Science coding tests, check out what others are saying about us:
“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.
“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.”
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.
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.
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.
