The Anatomy of A Data Science Interview

Data science interviews are particularly challenging as they cover a wide range of topics including programming, statistics, probability, and complex business problems.

Each of these skills is critical as the role of a data scientist is to translate a business problem into a mathematical one by taking existing data and processing it in a meaningful way in order to improve the business.

To test this diverse skill set, there are several types of data science interviews:

Applied Machine Learning Interview

The interviewer will present the candidate with a problem related to the interviewer’s company (e.g. “How do we improve engagement on Facebook?”) and ask the candidate how they’d set up an algorithm to solve the business problem. In this interview, you’d create a model of data that allows you to infer answers about unseen data or the nature of raw data. The central components of the candidate’s answer are feature engineering and their approach to cleaning, preparing, and training data to create a model to drive business insights.

Dataset Analysis Interview

The interviewer will give the candidate a data set and ask them questions about the data. Depending on your background, you may only be asked to write increasingly complex SQL queries or to go beyond simple queries and use a scripting language like R or Python to output a specific number or format the data set in a particular way.

More experienced candidates may be required to write a script to pull out features for a prediction task. The candidate may then be asked to plug those features into a machine learning algorithm. This type of interview essentially adds an implementation component to the applied machine learning interview.

Case Study Interview

The interviewer presents the candidate with a scenario through which they’ll need to talk about how to use data to solve the issue at hand. The candidate should be comfortable talking about metrics, applying simple predictive models, and discussing experimentation.

Take-Home Data Challenge

These challenges are among the most common screens for data science positions. The candidate will need to analyze a small data set and then write a report about the insights gained from their analysis. Typically, they’ll submit their code, explanations, and visualizations. If the candidate does well, they may then be asked to present their findings to the company’s data science team during an onsite.

Data science is about leveraging technical aptitude to create real-world practical insights, so you need to understand how business decisions are made and the insights people need. Whatever the interview type may be, you’ll need to:

• Understand the underlying question a person or company team is working on
• Translate the business problem into a mathematical one that data science can solve
• Consider and quantify tradeoffs of a feature in terms of metrics
• Solve the problem using math, statistics, database, and/or programming skills
• Convert your solution into an insight that a non-data scientist can use

It’s important to remember that interviewing is a skill of its own: even the best candidates struggle to communicate effectively under pressure within an interview setting.

Mock interviews are an essential tool for preparing for the pressures of a live interview. On Pramp, you’ll do back-to-back interview sessions, first as the interviewer and then as the interviewee, with a fellow job seeker. Not only will you get to practice verbally explaining your approach to a peer interviewer, but you’ll also get the chance to step into the shoes of the interviewer and evaluate a peer. Stepping into the shoes of an interviewer will help you gain invaluable insights into how you’ll be evaluated in a live interview.

From analyzing more than 100,000 interviews on Pramp, we’ve witnessed dramatic improvements in performance from a user’s first mock interview to their tenth, and beyond. Completing mock interviews on Pramp will help you overcome difficulties in communicating, reasoning, and putting your best foot forward during behavioral interviews.

Persistence, repetition, and consistency will be the key factors in determining a successful outcome of your interview preparation process. As with many other things in life, practice makes perfect; and for that, you have Pramp!