Optimizing your interview process: Learnings from over 100 data science interviews at Amazon

Joint Event on 5^th World Machine Learning and Deep Learning Congress and World Congress on Computer Science, Machine Learning and Big Data

August 30-31, 2018 Dubai, UAE

Andrew Jones

Victoria University of Wellington, UK

Posters & Accepted Abstracts: J Comput Sci Syst Biol

Abstract :

With the rapid increase in available data and computing power across businesses globally, the demand for data science and machine learning talent has surged. Businesses are at the cutting edge and have to do so as they need highly skilled candidates who can build, implement, scale and sell-in complex ideas and algorithms. Being able to identify and secure the best talent in this highly competitive and fast moving marketplace can be a difficult task. This presentation runs through learningâ??s from over 100 data science interviews at Amazon, one of the global leaders in the field. Itâ??s up to you as the interviewer to find objective evidence for the hiring decision, whether it be a yes or a no, it must be justified. If it is a yes, you will be working with this person day in day out and in most cases you will be accountable for their work and if it is a no, you want to be very sure if you are not missing out on a great candidate through misinterpreting their skill set or delivery style. To ensure you have got the right tools to start effectively interviewing data science and machine learning candidates, we will run through topics including; the value and limitations of CVâ??s, the value and limitations of coding/syntax tests, examples of effective and ineffective interview questions, what to listen out for in candidate responses, how to effectively probe for more information and how to deal with a perfect answer.

Biography :

E-mail: andrewjones54@hotmail.com