"-- Write your query here
select
marketing_channel,
avg(purchasevalue) as avgpurchase_value,
avg(case when purchasevalue > 0 then 1 else 0 end) as conversionrate
from attribution
group by 1
order by 3 desc
`"
Anonymous Roadrunner - "-- Write your query here
select
marketing_channel,
avg(purchasevalue) as avgpurchase_value,
avg(case when purchasevalue > 0 then 1 else 0 end) as conversionrate
from attribution
group by 1
order by 3 desc
`"See full answer
"Was given 90 minutes with an exhaustive set of requirements to be implemented as a full-stack coding exercise. It was supposed to have a UX, a server and a database to store and retrieve data.
The IDE was supposed to be self-setup before the interview.
The panel asked questions on top of the implementation around decision making from a technical perspective"
Aman G. - "Was given 90 minutes with an exhaustive set of requirements to be implemented as a full-stack coding exercise. It was supposed to have a UX, a server and a database to store and retrieve data.
The IDE was supposed to be self-setup before the interview.
The panel asked questions on top of the implementation around decision making from a technical perspective"See full answer
"Deep Learning is a part of Artificial Intelligence, it's like teaching the machine to think and make decisions on its own. It's like how we teach a child the concept of an apple - it's round, red, has a stem on top. We show them multiple pictures of apples and then they understand and can recognize an apple in future. Similarly, we feed lots of data to the machine, and slowly, it starts learning from that data, and can then make relevant predictions or decisions based on what it has learnt.
A co"
Surbhi G. - "Deep Learning is a part of Artificial Intelligence, it's like teaching the machine to think and make decisions on its own. It's like how we teach a child the concept of an apple - it's round, red, has a stem on top. We show them multiple pictures of apples and then they understand and can recognize an apple in future. Similarly, we feed lots of data to the machine, and slowly, it starts learning from that data, and can then make relevant predictions or decisions based on what it has learnt.
A co"See full answer
"Actually, all experiences in my life have been important so far. I say this with conviction since i consider myself a highly introspective person and often find ways to make myself more efficient. So, retrospection becomes very important for me. Still amongst them, the most valuable experience for me during my entrance exam preparation. I wasn't a good scorer and despite studying for the entire day couldnt score marks. It my self confidence to plummet. In the final days of the exam, i just told"
Trusha M. - "Actually, all experiences in my life have been important so far. I say this with conviction since i consider myself a highly introspective person and often find ways to make myself more efficient. So, retrospection becomes very important for me. Still amongst them, the most valuable experience for me during my entrance exam preparation. I wasn't a good scorer and despite studying for the entire day couldnt score marks. It my self confidence to plummet. In the final days of the exam, i just told"See full answer
Data Scientist
Behavioral
🧠 Want an expert answer to a question? Saving questions lets us know what content to make next.
"select
customer_id,
order_date,
orderid as earliestorder_id
from (
select customer_id,
order_date,
order_id,
rownumber() over (partition by customerid, orderdate order by orderdate) as orderrankper_customer
from orders
) sub_table
where orderrankper_customer=1
order by orderdate, customerid;
Standard solution assumed that the orderid indicates which order comes in first. However this is not always the case, and sometime orderid can be random number withou"
Jessica C. - "select
customer_id,
order_date,
orderid as earliestorder_id
from (
select customer_id,
order_date,
order_id,
rownumber() over (partition by customerid, orderdate order by orderdate) as orderrankper_customer
from orders
) sub_table
where orderrankper_customer=1
order by orderdate, customerid;
Standard solution assumed that the orderid indicates which order comes in first. However this is not always the case, and sometime orderid can be random number withou"See full answer
"First, let us start with the mission of Amazon: “We strive to offer our customers the lowest possible prices, the best available selection, and the utmost convenience.”
Alignment of recommendations system with Amazon's mission: Suggesting recommendations to the users would be a part of this mission as it would allow users to buy things on their mind for the lowest cost in market (may or may not be true). They might get better prices if they order adjacent items together. For example, i"
Nithesh S. - "First, let us start with the mission of Amazon: “We strive to offer our customers the lowest possible prices, the best available selection, and the utmost convenience.”
Alignment of recommendations system with Amazon's mission: Suggesting recommendations to the users would be a part of this mission as it would allow users to buy things on their mind for the lowest cost in market (may or may not be true). They might get better prices if they order adjacent items together. For example, i"See full answer
"Product Understanding -
Push notifications are pop up notifications received on the device (phone, tablet etc.) sent by various Meta apps whenever a new post has been made or a new message is received
Clarifying Questions -
Is is specific to one device?
Is it specific to one product?
Is it specific to one region?
Is it specific to one OS?
Is this as a result of changes to algorithm/UI?
Existing or a new feature?
Assumptions -
KPI calculation will only be for users who h"
Vishal S. - "Product Understanding -
Push notifications are pop up notifications received on the device (phone, tablet etc.) sent by various Meta apps whenever a new post has been made or a new message is received
Clarifying Questions -
Is is specific to one device?
Is it specific to one product?
Is it specific to one region?
Is it specific to one OS?
Is this as a result of changes to algorithm/UI?
Existing or a new feature?
Assumptions -
KPI calculation will only be for users who h"See full answer
"-- LTV = Sum of all purchases made by that user
-- order the results by desc on LTV
select
u.user_id,
sum(a.purchase_value) as LTV
from
user_sessions u
join
attribution a
on u.sessionid = a.sessionid
group by
u.user_id
order by sum(a.purchase_value) desc"
Mohit C. - "-- LTV = Sum of all purchases made by that user
-- order the results by desc on LTV
select
u.user_id,
sum(a.purchase_value) as LTV
from
user_sessions u
join
attribution a
on u.sessionid = a.sessionid
group by
u.user_id
order by sum(a.purchase_value) desc"See full answer
"Additional of COVID disclaimers to COVID related reels in instagram has helped users to navigate the crisis effectively as well as get the facts addressed regarding the vaccine."
U K. - "Additional of COVID disclaimers to COVID related reels in instagram has helped users to navigate the crisis effectively as well as get the facts addressed regarding the vaccine."See full answer
"Clarifying questions:
Is it before pre launch or for it's current business?
> Pre launch
Goals
> Adoption, engagement
Can briefly talk about:
What the company cares about? (Uber & Uber Eats)
Uber: Redefining the world moves for the better
Uber Eats: Make eating well effortless at any time, for anyone, anywhere
Expectations of consumers and restaurants/Stores
Consumers:
At one's comfort, one wants the groceries or/and food to be delivered to their"
Mahesh G. - "Clarifying questions:
Is it before pre launch or for it's current business?
> Pre launch
Goals
> Adoption, engagement
Can briefly talk about:
What the company cares about? (Uber & Uber Eats)
Uber: Redefining the world moves for the better
Uber Eats: Make eating well effortless at any time, for anyone, anywhere
Expectations of consumers and restaurants/Stores
Consumers:
At one's comfort, one wants the groceries or/and food to be delivered to their"See full answer
"There are many places where you can gather feedback.
We can divide the feedback from external and internal sources
External sources:
facebook
twitter
reddit
G2.
Internal sources:
on-app surveys or chats
support
Support engineers
Sellers
Recordings or notes from other PMs
However, you always have to talk with the customers so customer interviews are very important.
"
Sergio C. - "There are many places where you can gather feedback.
We can divide the feedback from external and internal sources
External sources:
facebook
twitter
reddit
G2.
Internal sources:
on-app surveys or chats
support
Support engineers
Sellers
Recordings or notes from other PMs
However, you always have to talk with the customers so customer interviews are very important.
"See full answer
"Q: How do we know that they spend too much time in the app?
A: User research/Qualitative survey
goal: decrease dissatisfaction that they spend too much time in IG
Persona's, lets segment based on usage:
New users: just signed up and getting the hang of it
lurkers: don't post or engage, just follow
contributors: post occasionally (stories + posts)
super users/micro influencers: post daily, engage with commenters, spend a lot of time in discover tab
IG mission statement is to capture and s"
Anonymous Hummingbird - "Q: How do we know that they spend too much time in the app?
A: User research/Qualitative survey
goal: decrease dissatisfaction that they spend too much time in IG
Persona's, lets segment based on usage:
New users: just signed up and getting the hang of it
lurkers: don't post or engage, just follow
contributors: post occasionally (stories + posts)
super users/micro influencers: post daily, engage with commenters, spend a lot of time in discover tab
IG mission statement is to capture and s"See full answer
"I can try to summarize their discussion as I remembered.
Linear regression is one of the method to predict target (Y) using features (X).
Formula for linear regression is a linear function of features. The aim is to choose coefficients (Teta) of the prediction function in such a way that the difference between target and prediction is least in average.
This difference between target and prediction is called loss function. The form of this loss function could be dependent from the particular real"
Ilnur I. - "I can try to summarize their discussion as I remembered.
Linear regression is one of the method to predict target (Y) using features (X).
Formula for linear regression is a linear function of features. The aim is to choose coefficients (Teta) of the prediction function in such a way that the difference between target and prediction is least in average.
This difference between target and prediction is called loss function. The form of this loss function could be dependent from the particular real"See full answer