Data Science Interview
Evaluate your statistics, machine learning, and coding knowledge.
Analyze a business case and show your business insight and communication skills.
Know the right preparation resources for Data Science interviews.
What I should know ...
What do we assess during the interview?
- In our data science interviews, we evaluate candidate knowledge in a wide ranges of topics including mathematics and statistics knowledge, coding (algorithm, data structure, and programming), machine learning, business insight, and communication skills.
- These areas might be evaluated separately or as part of a business case analysis where we discuss a real business question and we ask the candidate to explain how they analyse the problem.
- Case analysis questions usually start with a high level analysis and will be directed to more details to evaluate candidate’s knowledge in the above areas.
What's the difference between 'Technical focus' and 'Stat focus'?
- Technical focus is more for people with technical background and questions are more focused on business cases based on machine learning.
- Stat focus is more for people with Math and Statistics background and questions are more focused on statistical models.
- Both types are usually started with a business case and a general discussion on the approaching the question, then candidates are asked about ML or Statistical models that help answering the questions. Interviewers might ask some Stat and Math details to ensure the candidates have deep understanding of ML model. Finally, the interviewer might ask the candidate how they code based on a given data set.
Why are you recommended to do Data Science Interviews?
- Data science positions are referred to an spectrum of roles with a wide range of expertise. As a result, preparation for such positions will be challenging.
- A mock interview will help the candidate to evaluate their knowledge and skills in the main areas and find their strength and weaknesses. In addition, a mock interview is a close substitute for real interviews in a low stake environment.
- This environment helps candidates to practice to manage their stress and reduce their mistakes in their real interviews.
Why mock interview session with us?
- We have gathered a team of senior data scientists with years of experience in data science practice, leading data science teams, interviewing for their own companies and training junior data scientists.
- Our experienced interviewers provide a rich experience for candidates to help them in their transition to data science roles in their company of choice.
- At the end of each interview, candidates are provided with strengths and areas of improvement. Based on the interview result, we provide candidates with resources for further practices and better preparation for the actual interview.