scope:
started out as a DS, did a lot of data engineering, focusing on engineering problems
see's himself as a Data Engineer / SW Engineer who has a strong background with stats and ML
They'd use AWS S3 as cold storage, where most product data would live
collect data from all kinds of DB: postgres, mySQL, noSQL, AWS Dynamo, etc
do a lot of data cleaning and pre-processing using Spark/Hive
executing using AWS Glue or EMR,
chose the ML model based on the complexity of the problem (using Gradiant boosting, using XG Boost, etc)
business problem:
digital advertising company, they could have 300k qps, could only select which ones are good ones for their customers to show (ads), be able to predict advertising conversions
tech stack:
python
location:
sunnyvale
work auth?
yes, h1b transfer, about a year,
has i140 approved
scope: started out as a DS, did a lot of data engineering, focusing on engineering problems see's himself as a Data Engineer / SW Engineer who has a strong background with stats and ML
They'd use AWS S3 as cold storage, where most product data would live collect data from all kinds of DB: postgres, mySQL, noSQL, AWS Dynamo, etc do a lot of data cleaning and pre-processing using Spark/Hive executing using AWS Glue or EMR, chose the ML model based on the complexity of the problem (using Gradiant boosting, using XG Boost, etc)
business problem:
tech stack: python
location: sunnyvale
work auth? yes, h1b transfer, about a year, has i140 approved
comp $170k base