Workday Data Science Interviews
In 2012, Workday launched a successful IPO valued at $9.5 billion.
Workday is a leading provider of enterprise cloud applications for finance and human resources. It was founded in 2005. Workday delivers financial management, human capital management, planning, and analytics applications designed for the world’s largest companies, educational institutions, and government agencies. In January 2018, Workday announced that it acquired SkipFlag, makers of an AI knowledge base that builds itself from a company’s internal communications. In July 2018, they acquired Stories.bi to boost augmented analytics. These two acquisitions point towards an increased investment in the data science domain.
Interview Process
The process starts with a phone screen with a recruiter. That is followed by a technical phone interview with hiring manager. The questions are typical machine learning and data science questions — with some data structures and algorithms questions. If both of those go well, there is an onsite interview.
The onsite consists of five interviews with different team members, hiring managers, and executives. The questions are about programming skills, algorithmic skills, data structures, and anything related to machine learning techniques.
Important Reading
- Workday technical stack: Sneak peak into workday technical stack
- Workday-Prism-Analytics-: Prism analytics
- Data-as-a-Service: Global Data Platform
Data Science Related Interview Questions
- Given data from the world bank, provide insights on a small CSV file.
- Write a C++ class to perform garbage collection.
- Given 2 sorted arrays, merge them into 1 array. If the first array has enough space for 2, how do you merge the 2 without using extra space?
- Given a huge collection of books, how would you tag each book based on genre?
- Compare the classification algorithms
- Logistic regression vs neural network
- Integer array — get pairs of values that equal a certain target value.
- How would you improve the complexity of a list merging algorithm from quadratic to linear?
- What is p-value?
- Perform a tweet correlation analysis and tweet prediction for the given dataset.
Reflecting on the Questions
The questions are highly technical in nature. They point towards a very strong requirement of having Data Scientists who can code very well. Workday is the employee directory in the cloud and there are interesting things that could be done based on data. A good inclination of a Data Scientists in coding can surely land a job with Workday!
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