Model validation is a common quantitative finance job as it is needed by all banks due to regulations and solid investing firms should also have a solid validation team to reduce model risk and oversight. I this video I will break down my typical days (average, fun busy, bad busy, and slow), what a validation consists of work wise, and the skills needed to be a validator. This video is based on the current validation environment in the US. For example, SAS is the main language used however Python and R have been rising in popularity and I think they will play a bigger role in the future.
Some skills I didn't mention in this video are data management which is also becoming more important as banks move towards cloud technology. Common tools currently being use would be hadoop, hive, and spark.
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2 Days in the Life of a Risk Validator
https://youtu.be/_cvF8pknl5o
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