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Table of contents
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Table of contents

0:00
Знакомство с кандидатом
3:00
Функции бизнес аналитика и продуктового аналитика
4:54
Карьерный путь и мотивация
7:14
Интерпретация АБ тестов
8:36
Живой кейс про товарный остаток
11:10
Опыт видеоаналитики
13:22
Работа в команде и ценности
16:46
Качества “идеальной” команды
19:55
Кросс ревью аналитика
22:56
Карьерные пожелания
23:43
Видение тимлида и размер команды
25:15
Опыт собеседования в Яндекс
26:58
Проекты на следующий год
29:15
Карьерные перспективы в х5 и текущая работа
33:48
Куда не стоит идти работать
35:48
Обратная связь от Валерия
Video tags
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Video tags

Анатолий Карпов
Аналитика
машинное обучение
data science
SQL
база данных
Python
pandas
визуализация
карьера
зарплата аналитика
курсы
karpov courses
курсы по программированию
курсы по аналитике
курсы по стастистике
ML
stepik
data engineer
roapmap
роадмап
инженер данных
пути развития
карьера инженера данных
курсы карпова
карпов
machine learning
карьера в IT
работа в IT
дата сайнс
школа data science
Subtitles
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Subtitles

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  • ruRussian
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00:00:03
Hello Daria
00:00:06
How are you doing
00:00:07
great, but work has suddenly become a lot
00:00:11
now due to the fact that you are now a
00:00:14
leading data analyst
00:00:17
No, this is due to the fact that I
00:00:20
have the present tense on my resume
00:00:25
yes yes an analyst in the product and a leading
00:00:29
data analyst
00:00:31
there want something from me but how could it be that I’m
00:00:34
there part-time, here they want part-time
00:00:36
as full-time everywhere, it’s a
00:00:38
classic, it’s a classic, how did
00:00:42
it happen that you found yourself
00:00:43
torn between two?
00:00:47
Everything is very simple: in April, funding
00:00:50
for products was reduced specifically for mine
00:00:53
by 80 percent. Probably we need to start with
00:00:55
that where do you work really because
00:00:57
we somehow started right off the bat
00:01:00
then you know we’ll do the classics Daria
00:01:03
Tell a little about yourself My name is
00:01:06
Dasha I now work in 5 groups where
00:01:09
you actually brought me at one time
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and now I work as a data analyst at a
00:01:16
corporate warehouse data this is one
00:01:20
half of my bet and the other half of
00:01:21
my bet in the product we are making a product
00:01:24
for the commercial department of
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the intersection
00:01:28
[music]
00:01:29
we are calculating the optimal shelf length for
00:01:33
different categories of goods to
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satisfy the demand in a particular
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store sounds interesting
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that you have recently perhaps moved to a
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new apartment or not
00:01:50
but
00:01:51
but as far as I can see from your resume,
00:01:55
some are already talking about the fact that you have already
00:01:58
betrayed me.
00:02:00
With my support, I see that you
00:02:04
first worked as a business analyst.
00:02:05
Yes, you first worked as a business analyst in a
00:02:09
video analytics product, we developed
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video cash in X5 specifically. I am most
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of I strengthened my own ones, I used video
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analytics on empty shelves and video
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analytics of queues,
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video analytics of queues did not
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take off for us, firstly it was very expensive, and
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secondly,
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the decision was too often wrong,
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but video analytics of emptiness completely
00:02:35
took off, we carried out a pilot of a difficult
00:02:39
pandemic year 20, in the midst of
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a pandemic, we received a significant result, but
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unfortunately after the pandemic,
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a lot has changed, including the cost
00:02:51
of equipment and the project has ceased to be
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as effective as the
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company wanted it to be, they closed it, and what
00:03:00
does a business analyst actually do? I just
00:03:02
see the position is changing:
00:03:03
product analyst, business analyst, that is,
00:03:05
obviously these are different things, but I can’t
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say that I was a classic
00:03:10
business analyst because now
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I work with
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data like classic
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business analysts who come
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and study the process, say how it should
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look in a new way, and then pass
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it all on to development and, in general,
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development
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He and the business analyst communicate quite little about this, what he is
00:03:36
researching, as it were, Why is all this being
00:03:38
done? What are the business problems?
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What problems are we solving? What goals are we
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setting for ourselves? Plus, he deeply understands
00:03:46
how it all works in the product.
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Well, I don’t know that according to the classics. is
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product analytics or not, and also
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translated the test results into
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money and considered
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investment cases and the attractiveness of the
00:04:02
product for business, weren’t you
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tempted to translate so that
00:04:07
the project would still pay off even after the end of
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the pandemic?
00:04:11
Listen, but we made a lot of
00:04:13
attempts, but somehow You can’t take the words out of a song.
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You, of course, can make the product more
00:04:20
attractive at some point in the
00:04:22
stores.
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But this will only pay for part of the costs,
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anyway, if the costs are very high, no matter how
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you look at it, it wo
00:04:31
n’t work to reduce a minus to a plus. So, I have a
00:04:35
slightly different side of the question. Although it’s also
00:04:37
about money but in general, yes. In fact, you
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ask such questions, you see at the root of
00:04:43
manipulating the data in this regard and
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proving to investment analysts that
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the average We need to calculate exactly as
00:04:51
we need I can do it very well, it
00:04:53
means that Remember this, we will come back I
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see that your career, in principle, was
00:05:00
always connected with money in one way or another
00:05:01
Because you worked in a bank,
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opening
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you worked Then at the Bank of Russia as chief
00:05:09
economist,
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but in both places you worked for quite a
00:05:13
long time, but for two years, and in X5 You
00:05:17
will soon be working for 4 years Yes, that’s right
00:05:21
Yes, you are practically already at the current moment,
00:05:23
we can say that you worked at X5 for
00:05:24
the same amount of time as you worked
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at all your previous jobs.
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Yes,
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why, to be honest and frank,
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people will watch us. People
00:05:38
will have public interviews. So if you
00:05:41
want to be honest and frank, but
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first in Overall it was an interesting product,
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then at some point
00:05:47
difficulties arose and in fact, when it was
00:05:49
closed, my milestone of two years had passed
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since I’ve been working in one place, and then
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I just
00:05:57
had a question: What should I do next? I
00:06:00
could have stayed at X5 somehow move around X5
00:06:03
or you could go in
00:06:05
me, I looked at that moment to see that they were
00:06:08
offering me nothing super interesting there, I did
00:06:10
n’t find anything super interesting there, but in X5 it was as if
00:06:13
former colleagues who had worked with me before came to me and
00:06:15
said We need
00:06:17
product analysts I know you cool,
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let’s join us so I stayed X5 and in
00:06:23
general I changed my type of activity, I
00:06:26
changed my job, but at the same time I
00:06:29
remained within the framework of one company How do
00:06:31
you like working in retail compared to
00:06:33
working in banks I understood that it was more
00:06:35
dynamic That’s a plus in
00:06:38
banks it means it’s more
00:06:40
focused on monetary results
00:06:43
than in banks because in banks
00:06:46
we didn’t consider money as such costs
00:06:49
income expenses and so on
00:06:52
That is, oddly enough
00:06:54
in banks it’s more about money you’re now in
00:06:57
retail
00:06:58
And you like it, yes I like it
00:07:02
in general, I really liked the
00:07:06
city retail area and, for example, if I change my job
00:07:09
to banking, I wouldn’t want to go back. Well,
00:07:11
only if some kind of fintech
00:07:13
products are possible, then let’s go back to the issue of
00:07:15
calculating money.
00:07:17
The question is
00:07:19
this is all peak purely and speculation on my
00:07:22
part, I don’t know anything what actually happened there,
00:07:24
but surely on the part of the
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people who invested in this
00:07:29
product and were interested in its
00:07:31
success, video analytics was an attempt to
00:07:33
somehow Pressure so that the results were
00:07:35
turned to the right side after the
00:07:38
test, was there such a right side
00:07:43
so that we had more two times
00:07:45
the money, well, the question was not only in the
00:07:49
development of the product but in its useless
00:07:52
closure, so we
00:07:55
tried to calculate it in different ways. We
00:07:58
tried to continue this project. But at the
00:08:00
same moment, in fact, the
00:08:03
business customer who was
00:08:04
interested in this product approximately left. That is,
00:08:07
we have there the payback, in fact,
00:08:08
was right on the verge and it was possible to
00:08:10
push the product through. But since the
00:08:13
interested business customer left and the
00:08:15
new business customer
00:08:17
Well, he didn’t believe in the technology or that
00:08:21
it would bring money, he wasn’t interested
00:08:23
in any innovations of this kind, he
00:08:26
just I killed it all at the root, but yes, there
00:08:30
were attempts to calculate more successfully,
00:08:35
but they did not lead to anything. I am now
00:08:36
solving the same problem in my product.
00:08:39
We
00:08:40
did it, well, we rolled out the product to the entire
00:08:44
intersection and the question arose about the metrics
00:08:48
that we did not monitor and which we have
00:08:50
it wasn’t in the target ones what happened to it what kind of
00:08:53
meter is it if it’s not a secret
00:08:59
So now we are trying to understand
00:09:01
how much we really
00:09:03
influenced this metric and whether it was us
00:09:07
and whether everything is really that bad What
00:09:10
does the business think a It’s bad that the inventory
00:09:12
has increased Yes the goods in stock have increased, would
00:09:16
n’t this be visible in sales?
00:09:18
Well, that is, the commodity smell of what
00:09:20
comes in and is sold, but
00:09:23
it arrives and is sold, but it’s like you have
00:09:25
frozen money
00:09:27
[music]
00:09:30
just lying dead weight in the store And
00:09:33
that sales have fallen, no sales And what And
00:09:38
what did you do Tell me, that is, well, simply
00:09:40
Either sales fell or you began
00:09:42
to order more goods Do you
00:09:44
influence the ordering of more?
00:09:48
Point of view, we change the level of
00:09:50
assortment of certain groups in
00:09:52
the store and
00:09:55
depending on the level of assortment there are
00:09:57
different contents of the groups,
00:10:00
respectively, products that used to be
00:10:04
were laid out in the store according to planograms.
00:10:08
They left the assortment and now the
00:10:11
rest of them are lying in a warehouse, as it were, and are not for
00:10:14
sale, but
00:10:15
new goods are being laid out,
00:10:17
ordered, the usual process is going on, and
00:10:21
these old goods are called
00:10:22
non-stock goods and, accordingly, they are
00:10:25
also understood as stocks is growing
00:10:27
More precisely, it is not growing, it grew once
00:10:31
and is preserved. Do
00:10:34
you think they would have caused it or not?
00:10:37
Yes, we definitely caused it
00:10:40
and this is actually a normal process from the point of view of
00:10:43
what exactly
00:10:46
we did. Another question worries me
00:10:48
that in some stores
00:10:50
two months have already passed and for some reason the stores did
00:10:52
not sell out this inventory because
00:10:54
in the normal picture of the world, as far as
00:10:56
my colleagues and I understand the business process,
00:10:59
they should have been
00:11:01
sold out for two months, but for some reason this did not
00:11:03
happen, and now we have a question
00:11:05
for someone else operation block what went
00:11:09
wrong video analytics technologically
00:11:13
I still love a
00:11:16
magical complex product.
00:11:20
I understand that you
00:11:22
first encountered such a technologically complex product
00:11:24
in X5 because I
00:11:27
see
00:11:29
how you went through the adaptation period,
00:11:31
how difficult it was, it was simply
00:11:34
difficult, it was easy It’s difficult, some things
00:11:37
I haven’t fully understood yet. But
00:11:41
then we’ll say this:
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the responsibility of depending on the strengths of
00:11:48
the team. That is, I had a
00:11:51
product owner who was very well
00:11:54
versed in hardware, cameras, their
00:11:57
varieties, and so on. For example, I
00:11:59
still don’t know this science I found out and I don’t
00:12:02
really want to go deep into it
00:12:05
Why when the question arose
00:12:09
It’s really hard for me It’s
00:12:12
not my strong point
00:12:13
to understand the differences between video camera models
00:12:16
where what pieces of hardware are
00:12:20
suitable or not suitable for each other Well, it’s really
00:12:22
not my thing
00:12:24
and accordingly when the question arose
00:12:26
like Let’s make
00:12:28
the solution cheaper the question is how to reduce the cost of
00:12:31
support there or how to
00:12:33
redistribute the team’s resources so that the
00:12:35
team costs less, he
00:12:38
was mostly on my side. But how
00:12:41
to reduce the cost
00:12:42
from the point of view of hardware is the solution that was
00:12:46
dealt with by the owner. At first there
00:12:49
was a separate
00:12:51
manager for the whole business. But he’s like- then he did
00:12:53
n’t cope with his tasks very successfully,
00:12:56
he was eventually fired, he was fired, he
00:12:59
left on his own. Listen, I don’t remember exactly
00:13:02
how it was implemented, but
00:13:07
in general, he left the team and the team
00:13:10
wanted it, well, the team naturally
00:13:15
hoped that he wouldn’t watch.
00:13:17
That’s what
00:13:18
I think knows everything perfectly and so, but
00:13:23
this product owner who
00:13:24
understood technology after the
00:13:27
project ended, you didn’t want to
00:13:28
continue working with him because it seems like a
00:13:30
symbiosis that they could cover for each other.
00:13:31
Well, let’s just say we did
00:13:34
n’t have a Connection. And in the
00:13:40
future it was with him Well, I didn’t see
00:13:43
the point of working for myself, but why do you think
00:13:45
different values ​​didn’t happen?
00:13:47
I guess I would write this now just like
00:13:49
this: someone lives according to Aue and someone has
00:13:52
these kinds of values
00:13:55
Well,
00:13:57
not quite of course, but he just had
00:14:03
some moments that Naturally,
00:14:05
I don’t want to cover it to a wide audience in
00:14:08
which we did not agree, this created
00:14:11
additional stress for me
00:14:13
and, accordingly, in general,
00:14:17
stress for myself, I would not want to, I
00:14:19
would like to work more for
00:14:21
pleasure, and in principle,
00:14:23
now the team in which I work is
00:14:26
just all amazing We have full
00:14:29
Connection as with Perhaps you
00:14:32
will also remember the story: I first worked in a
00:14:34
bank and then worked at the Central
00:14:36
Bank of the Russian Federation and when I was
00:14:40
invited to the Central Bank, a team was just being formed there, a
00:14:43
department was just being formed and I took
00:14:45
one of my colleagues from the opening with me and
00:14:48
took
00:14:49
this here what is called Connection full
00:14:53
they think they are trying to somehow take this colleague
00:14:55
into X5,
00:14:57
but the colleague’s name by chance is not
00:14:59
Alexander
00:15:03
Yes, exactly Alexander, but in fact he
00:15:05
now continues to work successfully at the Central Bank,
00:15:08
now even as far as I know he is already
00:15:10
the head of the business that we
00:15:12
originally came
00:15:14
specialists,
00:15:15
everything is fine with him, now he’s trying to get
00:15:18
me back.
00:15:19
Let’s hope that the search will look at this
00:15:22
recording and take countermeasures
00:15:25
Well, judging by Because you’ve been here for almost
00:15:27
four years, you’ve now become aware of something about the
00:15:30
Team But the team said that everything
00:15:32
is great, everything’s fine
00:15:33
now having experience when you
00:15:37
had a strong team but somehow you didn’t get
00:15:39
along. That is, you admitted that the
00:15:41
sales person here was strong and understood how they did
00:15:43
n’t get along and there were teams with which you got
00:15:46
along. How could you
00:15:48
now, after just talking with people for
00:15:49
half an hour to understand whether you are being kept with them or
00:15:51
not, you have developed this magical ability in yourself,
00:15:56
no, you have
00:15:59
n’t developed the magical ability to understand in half an hour. But
00:16:02
usually, in about a week,
00:16:06
I already understand with a person, no. Although
00:16:10
I had someone like this, it’s correct in
00:16:12
statistics, it’s called
00:16:16
rather the opposite when I thought that it turned
00:16:18
out good it turned out bad when I thought it
00:16:21
turned out bad
00:16:24
Well, again, what to take for Positive It’s true that
00:16:28
this also happens
00:16:31
But in general Yes, now I look
00:16:35
first of all at the team and if I’m
00:16:38
not comfortable with them But if in the first half hour I’m not
00:16:42
comfortable then as if right away No, of
00:16:43
course it can be Full to snow them, but
00:16:45
it’s better not to risk the question as if
00:16:48
describing the team What qualities
00:16:50
should people have for you to
00:16:53
work well with them because with some it’s
00:16:55
comfortable Cool and with others it’s not so good,
00:16:58
although those are like strong knitting needles what is
00:17:02
missing that there must be
00:17:04
some kind of
00:17:06
openness and you know
00:17:13
not too much
00:17:16
self-confidence
00:17:18
That is, how a person should
00:17:23
calmly react to his own mistakes
00:17:26
and admit them as if to the mistakes of
00:17:28
others and allow them to be made Well and plus
00:17:31
the use of profanity
00:17:34
should be What
00:17:38
if you say I can’t work with
00:17:42
tourists with puritans those who don’t
00:17:44
swear I need them to swear
00:17:48
so many interesting things they will learn about
00:17:50
your previous grocery
00:17:53
[music]
00:17:54
we already see two people the
00:17:59
list is growing the list
00:18:01
should be
00:18:04
understanding that that all of us people look at
00:18:06
what question everyone makes mistakes and the right to make
00:18:09
mistakes. It’s not even just that there are mistakes. This is probably
00:18:12
the norm in how many there are
00:18:15
and how. What mistakes are probably even
00:18:17
several. Which ones or how?
00:18:20
I would say that the question is the repeatability of
00:18:24
mistakes,
00:18:25
as if you are one and
00:18:27
I made the same mistake twice Well, probably still ok at
00:18:31
3 already, well, it’s like
00:18:33
4 times I’m usually a cross for a person
00:18:38
in the sense that in this area This
00:18:43
person is not taught the
00:18:45
number of mistakes Yes, but again these are
00:18:49
all very relative indicators
00:18:51
depends on many factors, including the
00:18:54
load and the speed of work, and so
00:18:57
on. Because when something
00:18:59
requires you very quickly and very urgently
00:19:02
yesterday, for example, it is
00:19:04
clear that the likelihood of an error
00:19:06
increases and in general
00:19:10
this is a normal story. When a
00:19:12
person makes a mistake in such a time frame. Imagine
00:19:14
your entire team your department which
00:19:17
I have so far you know have experience managing
00:19:20
one person I had one
00:19:22
person like this video analytics now
00:19:24
a girl has joined the product instead of me because I am
00:19:27
completely switching to a data warehouse and
00:19:29
I am training her, plus a data warehouse
00:19:33
has introduced such a concept as cross-rivier
00:19:35
analysts, respectively, I review the
00:19:38
task of other analysts, in particular
00:19:42
one of our Junior, here he
00:19:44
periodically asks me questions in
00:19:46
fact. I really like sharing
00:19:48
my accumulated experience
00:19:50
and you know such general principles and
00:19:53
approaches to solving problems. How does
00:19:56
analytics work, what does it represent? Well, in general, in
00:20:00
fact, this is more of a
00:20:01
formal process. That is, you have a
00:20:03
task formulated by a
00:20:05
developer and you need, roughly speaking, with a
00:20:08
fresh look, to
00:20:10
see that all the sources are correct,
00:20:13
that the task is
00:20:15
formulated correctly,
00:20:17
that it is clear what the analyst wanted to say in this task
00:20:21
and what he wants the
00:20:23
developer to do. such Well, in
00:20:25
general, there is a checklist, more such
00:20:27
formal points. Is it possible to
00:20:29
do this if you don’t understand the context of
00:20:31
the product, an analyst came from the outside,
00:20:34
let’s say not to put up shelves, but a person
00:20:38
who is involved in pricing
00:20:41
and they look to see if he understands there is no one
00:20:47
inside the domain, that is,
00:20:49
you plus or minus, you know the sources they
00:20:52
work with, and the most difficult
00:20:54
cases are when creating a completely new
00:20:56
flow is still an
00:20:58
architect’s task. But to be honest, such tasks have
00:21:01
not yet happened because the
00:21:02
practice ticket is only at the end of October,
00:21:06
but in November no one develops new flows.
00:21:09
They actively begin
00:21:11
in January, but after the moratorium on
00:21:15
changes and after new budgets
00:21:17
were opened, and so on, as you immediately
00:21:20
smiled when talking about opening
00:21:22
new budgets, in fact, there are
00:21:25
several interesting
00:21:28
reports in the creation of which I would be
00:21:33
happy to participate. Well, so far everything is
00:21:35
going well the fact that I will participate is
00:21:36
good practice in your opinion, this is
00:21:39
cross-country or a waste of time, it’s not very
00:21:41
good practice because, to be honest,
00:21:43
well, I’ve been working in the data warehouse for
00:21:45
half a year already part-time, and when I started
00:21:49
reviewing the task of other analysts,
00:21:52
first of all, I noticed that I myself I
00:21:53
look differently and secondly, there are a
00:21:56
lot of some you know nuances. I
00:21:58
kept an eye on the little ones and
00:22:00
somehow I managed to switch to
00:22:03
full-time work there. I just came
00:22:06
to my manager in August and said that
00:22:09
guys, I want to leave completely to you, are you
00:22:12
satisfied with everything are you ready to
00:22:15
hire me full-time on the lights Yes
00:22:17
Cool Come on then it
00:22:19
actually started quite quickly as they
00:22:22
tell me The process of finding a replacement in the product
00:22:26
and I’m
00:22:28
almost Well, that is, I’m actually now already
00:22:31
working full-time at the EDV but it’s just that
00:22:33
the product goes to the Investment Committee, there are
00:22:37
a lot of very urgent questions, the new
00:22:39
girl is not so immersed, so
00:22:41
contact me for help and so I
00:22:43
help them on the second shift, so to speak.
00:22:45
Well, you transfer the case, and accordingly,
00:22:48
you get a statement about the fact that you are practically on the 2nd
00:22:52
half-time of work already close to the
00:22:55
end yes You like to pass on experience
00:22:58
What do you think about your career? Do you
00:23:01
want to continue to develop as a specialist
00:23:02
or do you want to
00:23:04
tell other people what to do? And
00:23:07
you would be paid money for this means At
00:23:09
this stage I want to
00:23:10
develop more in such topics that like a
00:23:13
playing coach That is, I don’t want to
00:23:16
completely go into
00:23:20
administrative management; I want to do something with my
00:23:22
own hands. But also,
00:23:24
how to start
00:23:29
developing towards managing people in a
00:23:31
team, I still want
00:23:35
full-time management. I see you
00:23:39
liked working part-time in
00:23:42
different places
00:23:43
but I would like to manage people team lead
00:23:49
somehow you see what it means Are these
00:23:51
different people different specialists or are they specialists in the
00:23:55
same direction more after
00:23:58
all specialists in the same direction
00:24:00
Well, that is, as if
00:24:03
I don’t want to be the owner of the product,
00:24:05
why Well, at least here in Expert
00:24:08
You know, I look at the
00:24:09
product owners and I feel a little sorry for them,
00:24:11
especially during the period when they go
00:24:13
to various investment committees because there are a
00:24:16
lot of
00:24:19
very different questions that need to be answered, both
00:24:22
technological and strategic, and
00:24:24
also for money. Please answer, well,
00:24:28
plus, after all, the team lead is like a player
00:24:29
coach, how to develop and train people, but
00:24:32
I can’t develop and train people in something
00:24:34
that I myself don’t know, I don’t know how, this is a bold
00:24:37
statement
00:24:39
with which many might disagree,
00:24:42
but I’ll probably agree with it,
00:24:46
what size team would be optimal for you
00:24:48
in this case, but at the
00:24:51
moment there are 2-3 people, two three people are
00:24:54
business analysts or product
00:24:56
analysts, rather product analysts. That is, you
00:24:59
know, in my resume, if you
00:25:01
look, it says that I am a product tonalist,
00:25:04
but I can’t yet understand what kind of
00:25:06
analyst I really am, because I’m kind of
00:25:09
not a complete business analyst and a
00:25:13
product analyst. I’m also not a complete
00:25:18
analyst because I went to Yandex. There are no product analysts who expect them to
00:25:22
conduct tests there almost
00:25:25
every day when I She said that I
00:25:27
don’t have such experience, I wouldn’t want
00:25:29
to do one of the continuous tests.
00:25:31
They said that, well, we still want
00:25:34
something else, so
00:25:36
we should know the text of the conversation,
00:25:39
which is quite strange, because Yandex
00:25:41
testing is practically
00:25:43
Automated, but I did
00:25:45
n’t know at that time now I
00:25:49
recognize you Thank you, next time I’ll know
00:25:51
what exactly to answer No, well, it happens,
00:25:53
as it happens, that some companies
00:25:55
claim that they have some kind of
00:25:56
platform, but they don’t, and sometimes they don’t claim they have it,
00:26:00
but Yandex has a very
00:26:04
strong one team testing and platform,
00:26:07
which is quite surprising Why did they
00:26:09
say this? And you talked to whom we
00:26:11
met,
00:26:15
as if on their own, they decided that it’s clear,
00:26:19
maybe they don’t know that
00:26:23
Well, good for X5, true and good,
00:26:29
perhaps the second reason why they took the
00:26:35
next stage is that I in general, I didn’t
00:26:38
explicitly state that I really want to leave,
00:26:41
I’m very
00:26:44
comfortable now where I am, it’s as if for
00:26:49
once I have clear
00:26:51
development prospects
00:26:54
and an interesting project for next year,
00:26:58
and what project for next year? Well, there
00:27:00
are several projects basically a
00:27:03
single warehouse of
00:27:05
automation data, various
00:27:06
reporting, in particular, they want to make a
00:27:08
report on confidential acceptance;
00:27:12
business analysts studied this
00:27:13
process and realized that it does not work exactly
00:27:15
as
00:27:17
originally planned; that despite
00:27:20
confidential acceptance, the store
00:27:21
recalculates the goods; you can
00:27:24
imagine how much
00:27:27
time this takes and so on So they decided
00:27:31
to change it a little so that stores
00:27:35
would not be interested in counting all
00:27:37
these pallets that come through
00:27:40
confidential acceptance,
00:27:42
that is, they will take a little more
00:27:44
money from RC and reduce the
00:27:48
motivational losses of the store Well, that is, it’s
00:27:50
really interesting to participate because
00:27:52
what a fantastically cool project that will
00:27:56
really help people,
00:28:00
tens of thousands of cashiers
00:28:03
in Pyaterochka,
00:28:05
not a single one. You know very well that
00:28:09
Pyaterochka always has something for a person
00:28:12
to do, plus there very often, according to my
00:28:16
observations, which are still not
00:28:19
representative, there is not an additional staff,
00:28:21
so it’s unlikely that anyone will throughout the
00:28:24
retail industry, he is always happy to hire
00:28:26
people, so he often has hiring advertisements in any store.
00:28:28
No, this is not because of
00:28:31
the advertisement on it, this is direct. When I
00:28:34
was doing video analytics, I talked a lot
00:28:36
with store directors
00:28:38
directly. So many of them said
00:28:42
that they have not up to the set now I was
00:28:44
again working on a similar project
00:28:46
at the intersection, but again we physically
00:28:48
changed something in the store
00:28:50
and again I talked a lot with the directors,
00:28:53
they again said that they don’t have the
00:28:55
set up anyway,
00:28:56
even if they allocate a new rate, where will
00:28:59
we get people from?
00:29:00
people don’t take this bet, they
00:29:02
don’t take it. Why if the analysts who
00:29:06
deal with this issue have a
00:29:08
separate Ichar domain and I’m sure they’re
00:29:12
working on this issue there. But I’m far from that.
00:29:14
You said career prospects are visible,
00:29:16
that is, after all, a career
00:29:20
prospect for you is who you are
00:29:23
what are you going to now, well, first of all, there are
00:29:26
prospects such as becoming the follower of a team
00:29:28
of several analysts, it’s true
00:29:31
there will be internal analysts X5 contractors
00:29:33
who will develop one
00:29:37
project, I’ll be like that from above
00:29:41
saying what to do, sharing experience and
00:29:45
seeing what they did there, it’s beautiful
00:29:48
Yes,
00:29:50
it sounds good That is, you want to
00:29:54
gradually become Tim whether the house is to teach
00:29:58
people. And what is your job after all? That
00:30:00
is, is it that you
00:30:02
write the code yourself or do you
00:30:04
communicate with people
00:30:08
in the product? It’s 50/50, that is, 50. We
00:30:14
often deal with this
00:30:16
today.
00:30:17
[music]
00:30:22
part of the time I communicate with people who are
00:30:26
customers there when we had a meeting
00:30:32
with the developers I explain or explain
00:30:36
how it should work
00:30:39
or ask the business how they would like
00:30:43
it to work in general goals
00:30:45
50 percent of the time in fact
00:30:48
I cheated a little that the
00:30:52
product analysts but my position to be
00:30:54
precise, it’s called the leading quality manager,
00:30:57
it happened because there were
00:31:00
organizational changes, I just had to be
00:31:02
shoved into some kind of position, that’s
00:31:04
where the rate turned out to be, they didn’t
00:31:06
push me away, I’m
00:31:07
called, although in fact it was
00:31:10
data quality I was working on a fairly
00:31:13
small percentage of my time, I was just
00:31:15
looking I made sure that
00:31:18
I needed the necessary sources of their correctness and wrote
00:31:22
scripts in Python and put them on a
00:31:25
schedule in Corona because the
00:31:27
product did not have the budget to have
00:31:30
its own infrastructure to properly deploy
00:31:32
Flow where Vops can be hired and so on.
00:31:35
In general, I wrote scripts that
00:31:38
collect data, react them and they put it in the
00:31:41
product base for further payments
00:31:43
on the part of ours,
00:31:46
and then give senties, they left in
00:31:48
April, at the same time when I was left
00:31:51
half of the plumbers left
00:31:54
The cranes flew
00:31:57
So from the business This type of
00:32:01
product you have is a cool one, but you need to do it a little
00:32:03
differently and I climbed into understand their scripts
00:32:06
and remake them so that they
00:32:10
Well, rather, set up crutches so that they
00:32:13
work in accordance with
00:32:15
business expectations remake ask with antists
00:32:18
this is a standard practice
00:32:21
widespread this is by the way also my
00:32:23
standard standard practice the
00:32:27
whole
00:32:28
area is holding up
00:32:31
you have now reassured me because I
00:32:33
honestly thought that I’m such a
00:32:34
unique specialist, or rather a person
00:32:37
who always gets these
00:32:39
crutches somewhere,
00:32:40
all your life you think that now you
00:32:43
’ll get rid of some crutches and go to where
00:32:45
people walk on their feet, you come there and
00:32:48
their crutches are even worse than what you had, don’t
00:32:51
worry, so don’t worry
00:32:53
So, well, you will get 1
00:32:56
rate instead of two 50 each
00:32:59
with a clear clear prospect of managing
00:33:04
people from the contractor’s side, that
00:33:08
is, the principle of babysitting them then. It’s
00:33:11
true, what will they do from X5, they won’t
00:33:15
quit, it
00:33:17
turns out there are
00:33:19
only advantages, that is, in fact, you
00:33:22
within 5 there were two different works, but if
00:33:25
you count the video, I saw the current work, it
00:33:34
turns out to be a lot. That is, it
00:33:39
turns out that you found yourself
00:33:41
and your plan for the article, a house of 34 people, and
00:33:46
within this sphere, working with them is
00:33:48
probably one of my last questions,
00:33:51
what was it for you It would be a
00:33:55
direct
00:33:58
black mark that you
00:34:00
shouldn’t go to work with these people in
00:34:04
this company, that is, we tried to discuss with you
00:34:06
Would you understand in 30 minutes that
00:34:08
these people are cool to work with? He said that it
00:34:10
would take a week. How do you understand that you don’t
00:34:13
need to go somewhere, what’s for you? absolutely
00:34:14
unacceptable except for the obscenities with which you,
00:34:18
nevertheless, worked for two years,
00:34:21
it’s not me who said that, notice what it’s
00:34:25
written about you in my resume. Listen, this is a
00:34:28
difficult question because I, for example,
00:34:33
know that I would definitely never
00:34:35
go to work at Magnit for anything in my life
00:34:37
Why is it that
00:34:40
we have a new girl who came from a magnet
00:34:43
and She confirmed all the rumors that are
00:34:45
circulating about how poorly the process is organized there, how
00:34:47
everyone is yelling at each other,
00:34:50
pushing responsibility, swearing, and
00:34:52
so on And besides the advantages,
00:34:59
we still don’t know what she will tell about the
00:35:02
X5 when coming X5 it’s true
00:35:04
she won’t tell this Well, this is brave,
00:35:09
brave, I hope
00:35:13
At least for now there is definitely no such thing Well
00:35:17
good Well In principle,
00:35:19
we talked for 40 minutes Almost
00:35:23
yes yes if we look
00:35:28
we started at 9:49
00:35:30
precision politeness of kings therefore If you
00:35:33
have any questions to me Before I
00:35:35
tell you what I got out of this conversation,
00:35:38
ask no. I’m very interested,
00:35:41
they ask about your company. So
00:35:43
we don’t have any company that we
00:35:45
interviewed. It’s true.
00:35:47
Well, look at what points you can
00:35:50
emphasize, I tried to deduce you
00:35:54
that you’re cheating you’re with calculations and you
00:35:57
basically said that
00:35:59
I’ll calculate it as it should be
00:36:03
Well, in general, one of my
00:36:06
key values ​​didn’t lie By the way, this is honesty
00:36:09
Yes, this again can be like
00:36:13
very good It depends on who’s looking for What The truth is, yes,
00:36:15
that is Maybe a product died on the
00:36:20
Internet grocery That’s how you need to
00:36:23
answer, and if I call someone from the
00:36:25
investment department, maybe you do
00:36:28
n’t even need to answer, well, it’s clear that
00:36:31
again, on the other hand, you said
00:36:33
Look, there’s
00:36:35
always a moment, as I understand it, there’s always
00:36:38
something said the Truth And also there is, as
00:36:40
you meant, And also what actually happened,
00:36:42
that is, it’s usually good when all this,
00:36:45
plus or minus, intersects strongly, but from
00:36:49
what I talked to you, I understand
00:36:51
that you tried to turn it this way and that way and that
00:36:53
way but without a special fly lying Because
00:36:56
you can’t make a
00:36:58
table from a single one But you can make
00:37:00
one there 09 That’s me so it could be
00:37:04
perceived as how I can do
00:37:06
anything there I’ll lie and so on, that is, from
00:37:09
what I understand you weren’t exactly trying
00:37:13
to cheat you tried especially hard to
00:37:15
just look at different
00:37:17
sections under a selection of stores and so
00:37:19
on. You said a little about this, but
00:37:21
in some stores it would have worked.
00:37:23
But there are a finite number of such stores
00:37:25
there on the verge of breakeven. This needs to be
00:37:28
clearly stated. That is, what do you mean?
00:37:31
I had no doubt
00:37:32
that you were cheating there or you were just looking
00:37:35
and are irreplaceable, just beat me into it as a
00:37:39
person, or rather, he doesn’t understand anything, which is not
00:37:41
far from the truth They say
00:37:43
we looked at different sections, we realized
00:37:48
that we looked, we counted it, we don’t
00:37:51
think much about what to do, it probably needs
00:37:52
some kind of money then a specific category there
00:37:54
they considered it becomes normal, but
00:37:57
let's buy a cheaper camera but it wo
00:38:01
n't work so well to some extent,
00:38:03
that is, because I can here, it means I'm
00:38:07
hiring my company, it means it wo
00:38:09
n't count for me as well as for the company,
00:38:11
the benefit for it is this it’s dangerous,
00:38:15
you know, yes. The second point is that I pulled some
00:38:18
things out of you, you
00:38:20
could say. Well, that is, I
00:38:22
asked some a lot of leading questions,
00:38:26
and ideally this should be a story about you
00:38:28
after which I practically, that is, I
00:38:31
want, I like this, I see myself as
00:38:35
that that is,
00:38:36
[music] a little bit
00:38:38
more
00:38:41
solo performance
00:38:44
so that I get this complete story from
00:38:47
you and not ask a clarifying question
00:38:51
because I may or may not
00:38:54
ask. The truth is, in my opinion, it’s good about
00:38:56
culture, that is that a good culture
00:38:58
Here is how you can moisten And so I
00:39:02
want to become Tim whether the house is so that this is
00:39:04
very easy I like to pass on
00:39:06
my experience to teach, but at the same time you mentioned
00:39:09
that you don’t like a
00:39:10
certain culture is to moisten a bowl I
00:39:13
like to teach And I also want to establish
00:39:15
such a culture in which people will be
00:39:17
comfortable, they will grow up, that is, put
00:39:19
this whole connection together, what
00:39:22
you don’t like, say, I’ve seen something like this in
00:39:23
my lifetime. I want people
00:39:26
not to see this. I’ll start this summer
00:39:29
and pass on experience and correct it to
00:39:33
prevent such things from happening. mistakes that were
00:39:34
made
00:39:36
and, by the way, your story
00:39:40
about this video analytics and money
00:39:42
you can just sell that now I
00:39:44
know how to count money
00:39:46
And now I understand how important it is And
00:39:48
that you need to go there in advance and now
00:39:51
I can save you a lot of money just
00:39:54
having cut to pieces
00:39:58
everyone that I thought a lot about How to
00:40:01
present my experience and I had this
00:40:03
idea, but why when we started talking about it
00:40:05
I didn’t remember about it Well,
00:40:07
this seems like a huge value in general,
00:40:09
take it, tell Valera, you know I
00:40:11
can certainly help you with the current project
00:40:13
do I have everything super power
00:40:15
What super power you don’t say Well, I
00:40:17
can look at the project and let you not
00:40:19
spend X millions or billions in
00:40:23
nowhere
00:40:24
what I can immediately say What
00:40:27
will be the margin in the limit and Is it worth it at all there
00:40:28
is a limit there two percent Well,
00:40:31
probably it can become minus 2
00:40:34
True, that is, if you expect
00:40:36
50 and in the end plus 10 Nokia if you
00:40:39
expect plus two In the end it could be 0
00:40:41
-2 -5, that is, this is how it
00:40:44
worked super well again. video analytics
00:40:47
video analytics
00:40:49
you’re not this is actually a great project in
00:40:53
terms of how much money was invested there with
00:40:55
billions invested
00:40:57
Well no billions in the end there weren’t
00:40:59
How many stores we had
00:41:03
but how many we
00:41:06
had cameras near the stores servers team yes
00:41:09
about a hundred
00:41:11
stores to equip with cameras equip with
00:41:14
servers write this software this is all for
00:41:16
two years, that is,
00:41:22
show the scale because if you
00:41:24
read the summary, look,
00:41:27
let’s say I read an analyst in the product,
00:41:30
I see a reduction in the costs of testing
00:41:32
one of the hypotheses 20 million rubles, but
00:41:34
at the same time, what is this about yours under the
00:41:37
analytics video there is no description of
00:41:38
some kind of gigantic product written at all. I still
00:41:43
perceive as my personal
00:41:45
mistake that it was simply a mistake
00:41:47
that in the end it became a product that it was
00:41:52
closed, so
00:41:56
let’s say it’s your fault and X5 will file a
00:42:00
lawsuit against you, but
00:42:02
if you think about it, you’ve already gained
00:42:07
this experience and now you can
00:42:09
capitalize it and sell it, really, that is,
00:42:12
you now know what you don’t need to
00:42:14
do. But I want to understand, in general,
00:42:17
what volume of business to fill the business
00:42:18
analyst said, we had such a
00:42:21
project, so many million, and what kind of
00:42:23
command did you have, that is, I tried to get it out
00:42:25
of what kind of team are you,
00:42:26
the product owner knew the equipment, cursed, that’s all that’s
00:42:30
all we know, and the fact that
00:42:33
you had three Grand Masters there were generally
00:42:36
top specialists in the world there,
00:42:39
probably at that moment this is one of the best
00:42:40
video analytics team in the world, a huge
00:42:43
scale of money, but that’s up to
00:42:46
you haven’t figured out the financial part at all, it’s extremely
00:42:48
important, this is generally the problem of a huge
00:42:51
number of startup companies, that they
00:42:53
make technology but don’t make money, and
00:42:55
this is what you absolutely didn’t sell to me, that
00:42:57
is, I listened there and some kind of video
00:42:59
analytics, something they thought didn’t
00:43:01
work out without the customer left
00:43:03
Another one came, he wasn’t interested in everything,
00:43:06
but in general, in fact, this story, if
00:43:10
we go back to the previous point,
00:43:11
sell How the story is connected, well,
00:43:13
it’s actually epic The canvas is
00:43:16
Epic, it really was the best
00:43:21
technology team in the world, why
00:43:23
weren’t they better there? 32 kg of a foreman, we
00:43:26
had a grocery worker who was incredibly
00:43:28
knowledgeable about technology, although he
00:43:31
swore, we
00:43:33
did projects like this,
00:43:36
we did a niche, we made queues, we made shelves, we
00:43:39
made
00:43:41
stores
00:43:43
[music]
00:43:44
and in the end, we only had one project that turned out
00:43:49
to be a small plus, so what next
00:43:53
there were problems, how would I approach him now,
00:43:54
look what a Mega experience I
00:43:58
can have you, there are some initiatives I can
00:44:00
understand You don’t have to go I can save
00:44:02
you from spending hundreds of millions cool, well,
00:44:06
it turns out I’m hiring Daria, I’m paying
00:44:09
and a million a million a month Well, what is it 12
00:44:12
million a year plus taxes Let it
00:44:15
save me 20 million a year or
00:44:19
300 well, in general it seems like a good investment
00:44:21
True, yes But I don’t And I ca
00:44:27
n’t do it Got accounting We’re building some kind of shelves there,
00:44:31
that is, it’s
00:44:34
clear that Yes, we are like a message for
00:44:36
life. You tell me how cool you are
00:44:39
from Cool yes, pass on the experience I
00:44:41
like it, I can
00:44:44
work here, I can work here, I can, you want to get into
00:44:47
the scripts, melt them down
00:44:50
from some nonsense, put together something that
00:44:53
works, the whole team left and
00:44:55
carried it alone we pulled it out, look at the
00:44:58
end, completely by accident Yes, there’s something there
00:45:01
again after What question about counting 5,
00:45:08
completely by accident, and then in fact
00:45:10
it turns out that you were the only one who dragged it
00:45:13
after people left the team
00:45:17
Well, this is a heroic act
00:45:21
and we found out about it completely by accident
00:45:26
True, in general, in the end we might not have found out a
00:45:29
whole bunch of things We probably didn’t
00:45:32
find out about, but
00:45:34
[music]
00:45:37
you have it all, you need it Yandex
00:45:41
said I asked the question somehow Yandex hasn’t
00:45:44
communicated well, it’s clear that you didn’t want to
00:45:46
go there on the other side but again, it was an
00:45:49
epic project, you heroically saved it with your
00:45:52
teeth, then pulled out two projects, you often
00:45:55
train people, you help.
00:45:58
Well, what I don’t like I don’t like
00:46:01
when there are some stressful things, but
00:46:04
the question is that there are so many of them, for
00:46:06
example, we are now preparing for
00:46:07
retirement new employees are all running around the committee,
00:46:10
of course, well, yes, I
00:46:12
can work the same if it’s 12 months of the year,
00:46:14
I’m so uncomfortable if it’s a month Yes,
00:46:17
that’s normal, everything is clear You can
00:46:19
cope And so there’s something there We also
00:46:21
found out that how the girl came out, that that’s
00:46:24
all now the poor unfortunate products are running around and
00:46:29
you could also say that I
00:46:31
support products that the poor
00:46:33
unfortunates answer technological
00:46:35
book questions, that is, what is the essence Yes,
00:46:38
everything is there,
00:46:39
and the texture and other stories But there is no general
00:46:42
narrative that would give it away,
00:46:44
so Well
00:46:46
[music]
00:46:48
I pulled it out how but notice how many
00:46:50
questions I asked
00:46:55
in general I the interviewer doesn’t like asking
00:46:57
questions like to listen to the story
00:47:01
because it’s hard to be late for a long time something
00:47:03
needs to be thought create a reasonable question
00:47:05
look avoid an awkward pause no
00:47:08
[music]
00:47:11
but in general
00:47:13
that is, everything is there you need to collect a single
00:47:15
story
00:47:17
Damn, it’s cool that we talked to you,
00:47:20
especially because you know my experience in
00:47:22
video analytics and But you just showed
00:47:25
me how this is possible from another, it’s necessary so
00:47:28
that a person who doesn’t know your experience in
00:47:29
video analytics simply understands this. The canvas
00:47:32
is real, but this is an epic story you I did
00:47:35
n’t say at all, for example,
00:47:38
what else did I deduce that I was there all my life in
00:47:40
banks, something came from a cell here,
00:47:42
horseradish technology, some kind of diplayer, not a
00:47:45
camera is simpler, and in general I was terrified, but
00:47:49
how did I get my hands on you? I took it there through my teeth I
00:47:51
also dragged it where all this was
00:47:54
where this heroic story was also
00:47:56
And where is this heroic story
00:47:59
Why I don’t know You know it just
00:48:02
seems like it’s a work moment Well, that
00:48:04
is, the fact that I came
00:48:06
some kind of technology that I did
00:48:09
n’t understand anything about before it turns out that you
00:48:12
can do it correctly That is,
00:48:14
what do you get? I have experience I can
00:48:16
start working there I haven’t worked before
00:48:18
I have experience It’s mega important to understand when
00:48:21
I’m with this
00:48:22
this is an important quality for employees
00:48:24
the truth is I’m saying it turns out I’m still
00:48:26
where can I give
00:48:28
and now I don’t know that Daria can pull
00:48:32
out a team I don’t know that Daria
00:48:34
can but technologies will collide I don’t
00:48:36
know that Daria worked on such a
00:48:37
gigantic project, that is,
00:48:40
nothing is said about the project about there, there is exactly
00:48:41
one number
00:48:43
there in the resume about 20 million and everything
00:48:46
that the video analyst takes hundreds of
00:48:48
I think the most billion could easily be the
00:48:54
person who counted this money
00:49:00
That is, putting all this together into a
00:49:03
single story will be
00:49:06
Cool Thank you very much thank you
00:49:09
and Apparently it’s already evening it’s already 5 evening
00:49:12
in Moscow and I congratulate you so much that for some reason it’s
00:49:14
dark outside the window in Moscow, well then have a
00:49:18
good evening I was glad to see you
00:49:21
Mutually See you later

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