Thank you for spending the time to work on this task.
We have received an overwhelming amount of submissions, and reviewing all the submissions takes more time than expected.
If you submitted the application form on time - you will be contacted shortly.
In the follow up interview you will be asked to demonstrate the working web-server and extend it. Make sure you understand all of the code presented in this repo (including Flask, HTMX, vecsim, etc.)
Please watch this video before your scheduled interview.
Thank you so much for your time, and keep in touch.
Original text follows:
Argmax is hiring Junior Data scientists.
This repo is meant to be a the first step in the process and it will set the stage for the interview.
We are a botique service company that specialize in recommendation systems.
Building a recommender system requires understanding many aspects of the user behaviour and item properties, and we utilize a variety of tools to do so (such as computer vision, natural language processing, time series, etc).
An ideal candidate would be someone who is proficient in python, curious and able to do independent research when necessary.
Our offices are in Ramat-Gan, Jabotinsky st. 155 and we work one day a week from there, the rest of the week we work from home or from clients' premises.
- Benjamin Kempinski on offline metrics
- Daniel Hen & Uri Goren on pricing with contextual bandits
- Ran Dan on column matching in databases
- Uri's webinar on Contextual bandits
Please read this notebook for background, motivation and submission instructions.