Data science is a quickly growing field that combines statistical analysis and computer science for applications in data mining, trend prediction, machine learning, and data modeling. Data science is utilized in almost all industries and is regarded as a transformative position due to the insight that it provides.
Many data scientists have graduate degrees in the field, but there are increasing opportunities for students to break into data science directly out of undergrad. Here are some accounts of individuals who did so:
- The New Grad Guide on Landing a Data Science Job
- A Year as a Data Scientist Right After College: An Honest Review
In order to break into data science, preparation in math, statistics, and computer science are all important. For most data science roles, a technical interview is a central part of the application process. This tests applicants’ abilities in data and quantitative analysis, as well as skill with programming languages, including R and Python. For more information on the technical interview and how to prepare, take a look at the following links:
- Cracking the Data Science Interview
- Data Science Interview Resources
- How to Prepare for Statistics Questions
In addition, watching sample data science technical interviews is a great strategy in order to prepare for the interview. Here are a few examples:
With the proper preparation and helpful insight, you will be on your own path to break into the exciting field of data science following your Yale undergraduate experience.