How To Get A Job In Data Science
A data scientist working in analytics can be expected to work closely with product teams in order to drive a product forward. There are several fundamental skills that are often needed in order to carry out such a role, and these are often broadly tested in interviews across a variety of companies. This post gives a broad overview of some tips and tricks for the overall interview process.
Five Tips for Data Science Interviews
Having been on both sides of the interviewing process many times, these are 5 tips for interviews that should be helpful to those interested in interviewing for data science roles.
1. When studying, focus on breadth without sacrificing depth
Data science interviews can be tough because depending on what kind of role you're interviewin
Machine Learning in Data Science Interviews
Overview
Machine learning questions are often the toughest parts of data science interviews, and for good reason. This post will highlight several example problems, general comments on machine learning, and what topics to study on the theory and application side.
5 Challenging Problems...
Statistics Guide for Data Science Interivews
Overview
Statistics is a core component of any data scientist's toolkit. Since many commercial layers of a data science pipeline are built from statistical foundations (for example, A/B testing), knowing foundational topics of statistics is essential. This post will serve as a basic guide for core topics in statistics, with some sample problems and solutions at the end.
SQL Guide for Data Science Interivews
Overview
As a data scientist, you will be working with data a great deal of your time and so will have to write many queries to retrieve it and derive meaningful information from it. SQL is one of the core skills to query data at any scale.
General Workflow...
Coding Guide for Data Science Interivews
Overview
Coding is important for data scientists, especially for those involved in putting their analyses into production. As such, many companies will test coding ability through basic data structures and algorithms questions. Topics include: arrays, trees, etc., along with algorithms such as BFS/DFS and dynamic programming. As with coding interviews, you are expected to understand runtime a