The right Data Science test to screen Data Scientists
Our Data Science tests are recommended for the following roles
- Informaticien junior
- Spécialiste des données moyennes
- Spécialiste des données
- Ingénieur en apprentissage machine
- Scientifique en apprentissage machine
- Architecte d'application
- Architecte d'entreprise
- Architecte des données
- Architecte des infrastructures
- Ingénieur de données
- Développeur d'intelligence économique
- Analyste de données
How our Data Science online tests work
Every DevSkiller Data Science online test is powered by the RealLifeTesting™ methodology. This in-house technology works by testing candidates with real-world working scenarios that they would likely encounter on their first day of work. What’s unique about this methodology is that it provides insight into the candidate’s practical coding skills, critical thinking, time management, instead of focusing on academic knowledge.
- Observer en temps réel le déroulement des tests du candidat
- Des tests à distance à la fois pratiques et rentables
- The RealLifeTesting™ methodology offers a greater candidate experience where candidates can use their own IDE, clone to GIT, run unit tests, and access Stack Overflow /GitHub / Google for research
- Data Science coding questions provide insight into the candidate’s practical skills, not just their academic knowledge
- Stringent anti-plagiarism tools
- Results are automatically generated report that non-technical professionals can understand
- Data Science coding questions for junior through to senior-level positions
Skills covered in DevSkiller Data Science tests
- Data analysis with Python
- Science des données
- Modélisation dimensionnelle
- Python 3.x
- Apprentissage automatique
- Structures de données
- Traitement des PDF
- Extraction des données
What to look for in a data scientist
Data Science is used primarily to make both decisions and predictions by making use of predictive causal analytics, prescriptive analytics, and machine learning. A data scientist is responsible for exploratory data analysis, machine learning & advanced algorithms, and data product engineering.
First and foremost, data scientists need to be critical thinkers in order to objectively analyze the data before forming an opinion or rendering judgment. Data scientists candidates should also be proficient in coding and be comfortable handling varied programming tasks. Although a broad knowledge of programming languages is preferable, Data Science is moving towards Python while R is also prominent. Proficiency in both mathematics and statistics is vital for a career in Data Science. Finally, experience with machine learning, deep learning, and AI is favorable for a data scientist candidate to possess. With the speed at which industries are moving in these areas, a data scientist must stay in front of the curve in research, as well as understanding what technologies to apply and when.
Vous voulez construire vos propres tests personnalisés ?
Did you know that you can create your own custom tests using the DevSkiller online task wizard? That’s right, creating your own fully customizable tests is easy with DevSkiller. Choose your test duration, number of questions, difficulty, and even upload your own codebase. Finding your next data scientist is easy with DevSkiller and our Data Science coding interview questions.
Interested in our Data Science coding interview questions but still aren’t sure?
We understand that making recruitment decisions for your company is not easy and should be considered before jumping straight in. If you’re still not sold on DevSkiller Data Science coding interview questions then hear what some of our satisfied customers have to say:
Veriday is a customer engagement and financial services technology (fin-tech) company specializing in products and solutions that transform customer experiences. Veriday hires approximately 40 developers annually. Before implementing DevSkiller, Veriday’s hiring process was long, tedious, and costly. The biggest problem they faced was wasting time and resources interviewing unworthy candidates. These candidates only reached the interview stage because the screening process was not covering any technical skills.
After implementing DevSkiller, Veriday was able to reduce the manual intervention required to send and assess the technical test. They were also able to reduce their tech rejection by 25%. With DevSkiller, Veriday now interviews 30 developers (instead of 50) for every 10 hires they make.
"Nous avons réduit le rejet des technologies, ce qui est très bien. Nous avons constaté une amélioration de 25% à ce stade après la mise en œuvre de DevSkiller. La plate-forme nous aide vraiment à évaluer les compétences en programmation des candidats et à fournir une approche logique des compétences en résolution de problèmes des professionnels de l'informatique. DevSkiller nous a fait gagner beaucoup de temps pendant la phase de montée en puissance et nous a permis d'inviter des candidats de bonne qualité qui ont obtenu de bons résultats au test, ce qui a fini par améliorer les critères de sélection".
Sabu Pappu – Talent Acquisition lead at Veriday
Foire aux questions
Qu'est-ce que RealLifeTestingTM ?
The RealLifeTestingTM methodology is the foundation of all DevSkiller online tests, including Data Science coding questions. It goes beyond games and algorithm puzzles to provide a 360-degree view of a developer’s skills. At its core, The RealLifeTestingTM stems from the belief that the best way to evaluate a developer’s development skills is with a work sample test that mirrors the actual development work they’ll do. Our online tests require candidates to build full project apps or add features to existing apps, just like they’ll be doing after being hired. To do this they will need to show their knowledge of coding, in stack resources, resources like Stack Overflow to find solutions and decision making to find the best way to solve the problems they encounter. The results you see show the candidate’s coding skill, decision making, code cleanliness, and problem-solving skills.
How are Data Science online tests evaluated?
The platform gets to work straight away after the candidate completes the tests evaluating the solution. Shortly after, the results are generated into a report that is easy to understand and share across teams and departments. Candidates are evaluated on whether the solution would run (an essential factor in all software development), whether there are any errors in the code, the quality of the code, and how it works in edge cases. There are also robust plagiarism features that show you how similar the results are to previous solutions.
Combien de temps faut-il pour mettre en place DevSkiller ?
You can send your first Data Science online test in as little as 5 minutes. DevSkiller’s extensive library of predefined online tests means that you can start testing your candidates right when you set up your account, no other work required.