Data Science Interview

After our admissions team has reviewed your application, you will have to complete three rounds of evaluation prior to admittance into our Data Science Immersive program - one technical exercise and two Technical Interviews. After your final interview, we will share an admissions decision within two business days.

During your interviews, feel free to ask questions, talk through your process and tell the interviewers when you’re stuck. We’re interested in your approach, ability to think through a problem and current knowledge.

Technical Exercise

The technical exercise is made up of three questions - one each in Python, SQL and statistics/probability. While there is no time limit, this exercise typically takes four hours to complete and must be submitted within seven days of receipt. Once you’ve submitted your exercise, our screening team will score it and reach out to you about next steps within two business days.

Python Interview

Using a collaborative code editor, you’ll work through solving a programming challenge in Python while an interviewer observes your work. Prior to this interview, you should be familiar with dictionaries, lists, control flow, data types and how to use them in Python. Additionally, it is important that you have a basic understanding of programming principles, experience working on the command line, understand basic flow/logical states and can write simple functions in Python.

If you’re close but do not meet our Python admittance standards, we may ask you to attend Week 0 to review Python fundamentals before we make a final admissions decision.

Math, Probability and Statistics Interview

Working with an interviewer via Google Docs, you’ll solve challenges in statistics and probability. Challenges may include topics like model fitting, regression analytics and probability.

Additionally, it is important that you have an understanding of independent and conditional probability, expected value, probability distributions, hypothesis testings and confidence intervals. Having experience with multiple linear regression, logistic regression, statistical modeling, basic visual methods and model evaluation will also be beneficial.

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Get Started Today

Start your career in Data Science today! Apply for one of our upcoming Data Science Immersive course dates.