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Slack - Data Scientist - Take Home Assignment

[复制链接] |只看干货 |slack, 数科面经, 分析|数据科学类, 面试经验
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2018(7-9月) 分析|数据科学类 硕士 全职@Slack - 网上海投 - Onsite  | Other | 在职跳槽

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Time: You should feel free to spend as much time on this assignment as necessary to feel comfortable with your answers. In general, candidates typically spend somewhere between 1 - 2 hours.
Background on the Data:
Slack has a system that allows apps to send alerts to Slack users in 3 channels (banner, push, sidebar).
We log two separate events into a table called alerts:
1. Whenever a user sees an alert (impression or 'imp')
2. Whenever a user clicks on an alert ('clk')
The table contains data for a single day. This logging is new and hasn't been vetted yet. Trust nothing, callout bad data, and work to clean the data as necessary to get the best answer.
Columns in the table:
user_id: numeric, unique and persistent id for each user
team_id: numeric, unique and persistent id for each team. Each userid belongs to exactly one team.
app_id: numeric, unique and persistent id for each app
event: string with values 'imp' (as in impression, so it was seen) or 'clk' (the user interacted with it)
primary_browser: string, the browser the user was using
alert_type: string, alert was in a banner/sidebar/push
eventtime: the timestamp of when the interaction happened
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Grading Rubric:
When we grade these assignments we consider the following:
  • Is the SQL correct?
  • Is the SQL concise and easy to read?
  • Were appropriate metrics chosen, where applicable?
  • Were flaws in the data noted and engineered around appropriately?
  • Were the results communicated clearly and concisely?
  • How long did it take to complete the exercise? [to be fair to candidates who are time constrained we like to be aware of this]

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