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Bny taken all 3 interview on Saturday & cleared all. #1 Code pair + technical #2 Cross functional #3 Bar raiser . On Monday, HR asked me to send require documents but not scheduled any HR discussion call. I sent docs to HR. Is there any HR discussion call happening in BNY ? How much time BNY takes to release offer post document submission/HR discussion ? BNY Mellon | Pershing Bny mellon technology BNY Mellon BNY
Hi Fishes
I would like to know about the client interviews (especially in data science or machine learning roles).
Are these interviews tough?
Are these interviews meant to assess technical knowledge? For example, what is binomial distribution, what are different data structures in python, ml algorithms etc.
I would request each of the nagarrians to share their thoughts irrespective of the technologies you are working.
I am thankful to you for taking time and helping me out.
Nagarro
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I think cognizant has the worst HRs, like i dropped an email a couple of weeks ago to re-negotiate my offer but they didn't care to respond. I dropped an email saying I am withdrawing my offer and they still didn't care to respond. Why are they hiring if they don't care? Deloitte USI Tata Consultancy Wipro Accenture India Infosys
Looking for a switch. Any leads?
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One of us, one of us....
Sounds kinda easy tbh, the way I’d answer it is I would say (from a purely mathematical perspective) that, considering both 𝐴
A
and 𝐵
B
are random variables, variable 𝐴
A
influences variable 𝐵
B
if and only if they are not independent, i.e. if
ℙ(𝐴=𝑎 and 𝐵=𝑏)≠ℙ(𝐴=𝑎)⋅ℙ(𝐵=𝑏).
P
(
A
=
a
and
B
=
b
)
≠
P
(
A
=
a
)
⋅
P
(
B
=
b
)
.
The (un)equation basically says that "information about 𝐴
A
and 𝐵
B
considered together" is not completely determined by "information about 𝐴
A
alone" and "information about 𝐵
B
alone".
In other words, there is no interaction between 𝐴
A
and 𝐵
B
which we need to take into consideration when trying to deduce "information about 𝐴
A
and 𝐵
B
considered together" from "information about 𝐴
A
alone" and "information about 𝐵
B
alone". I.e., 𝐴
A
and 𝐵
B
together are "just the sum of their parts" and are "not greater than the sum of their parts".
(Of course we have to use multiplication instead of addition, since probabilities are bounded between 0
0
and 1
1
inclusive, and multiplication of such numbers is closed under multiplication but not addition.)
The statistics comes in because we do not have perfect knowledge of the universe, so we do not know exactly whether 𝐴
A
and 𝐵
B
"really are" random variables, and even if we did, we do not have perfect enough knowledge of 𝐴
A
and 𝐵
B
to say with absolute certainly whether the above formula does or does not hold.
In other words we do not know exactly how to consider them as random variables even if we knew with certainty that they were random variables, so the definition given above doesn't necessarily make sense without a lot of interpretation (since the definition requires us to consider 𝐴
A
and 𝐵
B
as random variables, which we don't necessarily know how to do "in the best way").
So (according to my rudimentary understanding of statistics) we employ statistical models to try to model 𝐴
A
and 𝐵
B
as random variables, and we use statistical tests to see how much those statistical models "make sense".
In particular, using theoretical considerations, we can know with "absolute" certainty, if an assumption is actually correct, what consequences must necessarily follow from that assumption. If our statistical tests show that it is somehow "unlikely" that these consequences hold, then we can conclude that it is also "unlikely" that our statistical model for 𝐴
A
and 𝐵
B
is correct.
(This is because any logical statement is equivalent to its contrapositive: statement p is true implies statement q is true if and only if statement q is false implies statement p is false. Statistical tests allow us to gauge whether statement q (the consequence of a statistical model) might be false, and thus whether statement p (the statistical model) might therefore be false.)
The math questions involved the proportions of two variables changing and how they would impact a different metric, so it was not a super simple math question
They care more about your thought process than seeing a correct answer, it’s not over