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Channel

Data Science Jobs

@datascienceml_jobs

On this record: Topic · Observations · Growth · Engagement · What this channel posts · Reactions · Advertising · Posts · Posts recorded as deleted · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry

21,640subscribers

+708 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001601022378
TypeChannel
Username@datascienceml_jobs
Descriptionадмин - @workakkk @ai_machinelearning_big_data - Machine learning @itchannels_telegram - 🔥лучшие ит-каналы @pythonl - Python @pythonlbooks- python книги📚 @datascienceiot - ml книги📚 РЕЕСТР РКН: clck.ru/3Fmrbd
CreatedBetween 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live12 November 2026
Measurements held65
Confirmed unchanged1 time, most recently 12 November 2026
On Telegramt.me/datascienceml_jobs

Topic

Job listings — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 20 August 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear in near-verbatim form on 2 other registered channels. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@datascienceml_jobs/1854 · this entry15 Jul 2026, 13:51 UTC@datasciencejobs/333013 Aug 2026, 09:37 UTC1.0029 days
@datasciencejobs/33511 Sept 2026, 09:02 UTC@datascienceml_jobs/1890 · this entry15 Sept 2026, 09:05 UTC1.0014 days
@datasciencejobs/336214 Sept 2026, 08:14 UTC@datascienceml_jobs/1891 · this entry15 Sept 2026, 10:20 UTC1.0026 hours
@datascienceml_jobs/1911 · this entry1 Oct 2026, 13:28 UTC@datasciencejobs/33965 Oct 2026, 09:00 UTC1.004 days
@datasciencejobs/341321 Oct 2026, 07:29 UTC@datascienceml_jobs/1930 · this entry21 Oct 2026, 10:35 UTC1.003.1 hours
@datasciencejobs/343510 Nov 2026, 10:04 UTC@datascienceml_jobs/1942 · this entry10 Nov 2026, 10:37 UTC1.0033 minutes
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
ChannelMatching postsText overlapTypical gapPublished first
@datasciencejobs10 (8/8 hand-verifiable sample passed)1.003 days@datasciencejobs (7–3)
@datajobschannel8 (8/8 hand-verifiable sample passed)1.003.6 hours@datajobschannel (6–2)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 12 of the 13 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.

“Published first” means first in this corpus. We hold 83 comparable posts for this entry, running 23 June 2026 to 12 November 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Recorded under the key clone_copy, last confirmed 13 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Growth

20,93221,64421,28821,6406 August 202612 November 2026
65 measurements spanning 98 days, net +708. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 20,825–21,751 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 65
Measured (UTC)SubscribersChange
12 Nov 2026, 14:1621,640-2
10 Nov 2026, 14:2021,642+2
8 Nov 2026, 23:5821,640-4
7 Nov 2026, 19:4721,644+6
6 Nov 2026, 18:4621,638+13
5 Nov 2026, 18:1721,625+14
4 Nov 2026, 21:1421,611+7
3 Nov 2026, 22:1021,604-1
2 Nov 2026, 20:2021,605+6
1 Nov 2026, 17:4521,599-13
31 Oct 2026, 20:2821,612+11
30 Oct 2026, 20:3821,601+1
29 Oct 2026, 19:1021,600+9
28 Oct 2026, 19:4121,591+2
27 Oct 2026, 16:4621,589-2
26 Oct 2026, 18:1721,591+1
25 Oct 2026, 15:2921,590+2
24 Oct 2026, 14:5621,588+3
23 Oct 2026, 17:1521,585+12
22 Oct 2026, 14:4921,573first reading

Engagement

85 posts held, back to 23 June 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 87 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
12.2%
avg views ÷ 21,640 subscribers
Avg views / post
2,650
21 posts measured
Reaction rate
0.301%
reactions ÷ views · ER floor
Posts in window
21
of 85 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 19 of 21 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 12 November 2026
Posts held85 (23 June 2026 – 12 November 2026)
Views total55,580
Reactions total151
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken13 Nov 2026, 04:14 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Photos
52
Videos
3
Links
530

Lifetime counters from Telegram’s own channel header, read 13 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Video runtime
53s
Average length
27s

Measured directly from 2 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.

Reaction mix

705 reactions across 74 posts, in 28 distinct kinds. The most used accounts for 35.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🖕25335.9%
💊10815.3%
🤣10214.5%
❤628.79%
😁496.95%
👍365.11%
🥴233.26%
🔥212.98%
🤔121.70%
🤨60.851%
😡50.709%
❤‍🔥30.426%
🌚30.426%
🍌30.426%
🐳30.426%
😍20.284%
😴20.284%
🥰20.284%
✍10.142%
🌭10.142%
8 further kinds81.13%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 78 of the 85 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 795 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 85 most recent posts we hold, published 23 June 2026 to 12 November 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Advertising

Ad load
12.9%
11 of 85 posts carry an ad marker
Regulatory tokens
11
posts carrying an erid · 11 distinct tokens
Median views · ads
2,580
over 11 measured posts
Median views · rest
3,100
over 74 measured posts

An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.

This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.

Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. They are printed side by side with the count behind each rather than as a ratio: an ad and an ordinary post are not otherwise matched — for topic, for length, for hour of day — so the gap between them is a description of two groups and not the effect of one being an ad.

Advertising tokens recorded on this entry
eridPostsFirst seenLast seen
2VSb5yHYHXY117 September 202617 September 2026
2VtzquY5GHU110 November 202610 November 2026
2VtzqujpVeT131 August 202631 August 2026
2Vtzqv48qtp116 September 202616 September 2026
2VtzqvvSNRk15 November 20265 November 2026
2VtzqwmU2gs119 August 202619 August 2026
2VtzqwzhWdT114 October 202614 October 2026
2VtzqxEGaWg128 September 202628 September 2026
2W5zFGRxozi112 November 202612 November 2026
2W5zFHUC8ad114 August 202614 August 2026
2W5zFJSkT7P115 September 202615 September 2026

A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.

Measured over the 85 most recent posts we hold, published 23 June 2026 to 12 November 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.

Recent posts

Telegram’s own ‘edited’ marker: 1 of 21 posts held from the last 30 days (4.76%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

12 Nov 2026, 12:16 UTC≈1,070 views5 reactionsread 13 November 2026

Мы в АО «Bereke Bank» ищем Senior Data Scientist — человека, который ведёт модель от постановки задачи до мониторинга и не теряет к ней интерес после релиза. Для кредитных рисков (розница и корпоративный бизнес), портфельные модели, взыскание (soft/hard collection) и антифрод. Что предстоит: ▪️ самостоятельно вести DS-решения от идеи до production ▪️ вместе с бизнесом формулировать и проверять гипотезы ▪️ разбиратьс…

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12 Nov 2026, 09:06 UTC≈1,240 views2 reactionsread 13 November 2026
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10 Nov 2026, 12:37 UTC≈1,760 views3 reactionsread 13 November 2026

#вакансия Позиция: Главный аналитик данных (Управление развития кросс-блочных продаж) Компания: Альфа-Банк Формат работы: гибрид (офис + удалёнка) Город и офис: Москва, м. Технопарк Занятость: полная 🌟 Чем предстоит заниматься: — Анализировать продажи РКО и зарплатных проектов (ЗПП): динамику, портфель, ключевые драйверы и точки роста; — Исследовать клиентский портфель РКО и ЗПП: структуру, активность, доходность…

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10 Nov 2026, 10:37 UTC≈1,390 views8 reactionsread 13 November 2026
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6 Nov 2026, 11:14 UTC≈2,490 viewsread 13 November 2026

Ищем Senior BI-разработчика / аналитика – Apache Superset, HR Проектная работа: завершить три HR-дашборда птицефабрики и довести их до приёмки заказчиком: – Списочная численность – Движение и текучесть персонала – Переработки Что нужно сделать – Изучить материалы, уточнить требования и оценить объём работ – Согласовать HR-метрики и самостоятельно разработать SQL-витрины и бизнес-логику расчётов с учётом кадровой ис…

5 Nov 2026, 17:04 UTC≈2,490 views3 reactionsread 13 November 2026
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5 Nov 2026, 09:04 UTC≈2,410 views1 reactionsread 13 November 2026

📄 Backend-разработчик (Middle / Middle+) Компания - AИ МОП 💰 удаленно · полная занятость 💎 AI МОП делает голосовых ИИ-агентов, которые сами разговаривают с клиентами и продают. Здесь backend работает с живыми звонками: ошибка в коде может оставить клиента без звука или запустить повторный звонок. 📌 Задачи: - развивать сервисы на Python и FastAPI в большом продукте с несколькими командами - поддерживать телефонию: …

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3 Nov 2026, 12:40 UTC≈2,490 views4 reactionsread 13 November 2026

Технократия Data Engineer 🌍 Казань (релокация) Мы создаём финтех-продукты для рынков, где формируется будущее финансовых технологий. Работаем на международных проектах, совмещая скорость стартапов с надёжностью enterprise-разработки. Чем предстоит заниматься? • Проектировать и поддерживать интеграцию источников данных (взаимодействие с процессинговыми системами и Автоматизированной Банковской Системой / АБС); • Орг…

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3 Nov 2026, 10:37 UTC≈2,510 views7 reactionsread 13 November 2026

Разработать ML-решение, которое аффектит сразу на миллионы пользователей и на бизнес? Это в Ozon Tech. Ребята как раз запустили Fast Track для некоторых вакансий — все этапы собесов займут до 5 дней. Куда можно пройти побыстрее: – в команду ранжирования, совершенствовать поисковую выдачу – в команду рекомендаций, развивать логику и точность ранжирования – в команду нейросеток, улучшать и масштабировать модели – в ко…

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30 Oct 2026, 10:13 UTC≈3,280 views12 reactionsread 13 November 2026

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27 Oct 2026, 09:00 UTC≈3,520 views24 reactionsread 13 November 2026

#senior #300k #удаленка IT-Implant Data Scientist (Middle+/Senior) от 260 000 до 290 000 ₽ за месяц, на руки Опыт работы: 3–6 лет Полная занятость График: 5/2 Формат работы: удалённо ☑️ Чем предстоит заниматься -Формулировать и декомпозировать бизнес-задачи в ML/аналитические решения -Проводить исследовательский анализ данных, проверять гипотезы и выбирать подходящие методы -Разрабатывать и валидировать модели: кла…

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22 Oct 2026, 16:40 UTC≈3,930 views7 reactionsread 13 November 2026

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Showing the 12 most recent of 85 posts we hold for @datascienceml_jobs. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Posts recorded as deleted after publishing

We recorded 4 posts on @datascienceml_jobs as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.

A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.

First seen missing
16 August 2026
Most recent seen missing
3 November 2026
Median time before seen missing
9 days
Seen missing in the last 30 days
1

Forward network

Republishes

Channels on the register whose posts this channel has forwarded.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

Channels on the register whose posts name this channel's handle.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Channels Telegram recommends alongside this one

Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.

ODS #jobs
@odsjobs · 14,599
#1
Data Science Jobs
@datasciencejobs · 22,621
#2
Machine learning Interview
@machinelearning_interview · 30,562
#3
Machinelearning
@ai_machinelearning_big_data · 275,343
#4
Data jobs — вакансии по data science, анализу данных, аналитике, искусственному интеллекту
@datajob · 15,159
#5
Data Secrets
@data_secrets · 96,159
#6
Dev & ML Connectable Jobs
@dev_connectablejobs · 29,105
#7
Анализ данных (Data analysis)
@data_analysis_ml · 51,973
#8
Нескучный Data Science Jobs
@not_boring_ds_jobs · 9,473
#9
Нескучный Data Science
@not_boring_ds · 12,077
#10
Data jobs feed
@datajobschannel · 12,646
#11
Job for Analysts & Data Scientists
@foranalysts · 37,857
#12
Data Science 🛸 & ML Jobs за рубежом
@opento_data · 7,784
#13
Машинное обучение RU
@machinelearning_ru · 18,334
#14
Python Jobs
@python_djangojobs · 15,132
#15
Data Secrets | Карьера
@data_secrets_career · 7,412
#16
Big Data AI
@bigdatai · 18,324
#17
🏆 AIeron | Data Feeling
@datafeeling · 14,202
#18
Dealer.AI
@dealerAI · 17,199
#19
Институт AIRI
@airi_research_institute · 13,977
#20
Python вопросы с собеседований
@python_job_interview · 24,885
#21
Data Science. SQL hub
@sqlhub · 36,003
#22
Data engineer / SQL работа
@datascjobs · 5,740
#23
Start Career in DS
@start_ds · 11,460
#24
Data Science
@datascienceiot · 42,462
#25
Python/ django
@pythonl · 58,245
#26
Библиотека дата-сайентиста | Data Science, Machine learning, анализ данных, машинное обучение
@dsproglib · 18,289
#27
Аналитик данных
@dataanlitics · 6,386
#28
Зарплатник Аналитика
@zarplatnik_analytics · 11,694
#29
Phystech.Career
@phystechcareerchannel · 7,632
#30
Машиннное обучение | Наука о данных Библиотека
@machinelearning_books · 16,950
#31
Библиотека собеса по Data Science | вопросы с собеседований
@ds_interview_lib · 4,459
#32
ML for Value / Ваня Максимов
@ml4value · 5,671
#33
Data Science | Machinelearning [ru]
@devsp · 19,651
#34
🏄 Соревновательный Data Science | Kaggle | Чемпионаты
@data_science_winners · 3,366
#35
Connectable Jobs
@zarubezhom_jobs · 106,423
#36
Your Dream Data Job
@dreamdatajob · 1,428
#37
Complete AI
@complete_ai · 7,887
#38
Mashkka про Data Science
@mashkka_ds · 5,306
#39
ML / DS_Jobs
@ml_data_science_job · 2,339
#40
Ит Вакансии / Работа программиста
@hr_itwork · 11,110
#41
Тагир Анализирует
@tagir_analyzes · 11,641
#42
Data Analytics Jobs | Вакансии
@data_hr · 11,171
#43
Data Job | Data Science в Германии 🇩🇪
@datajob_io · 881
#44
Python RU
@pro_python_code · 12,295
#45
Artificial Intelligence
@ArtificialIntelligencedl · 16,815
#46
AI VK Hub
@aihubvk · 2,485
#47
(sci)Berloga Всех Наук и Технологий
@sberlogabig · 8,021
#48
Data, Stories and Languages
@datastorieslanguages · 3,922
#49
MLinside - школа ML
@ml_inside · 4,088
#50
Data Engineer Работа Вакансии
@de_rabota · 5,263
#51
Пристанище Дата Сайентиста
@renat_alimbekov · 6,287
#52
DziS Science | Data Science
@dzis_science · 2,191
#53
Инжиниринг Данных
@rockyourdata · 23,679
#54
Chad Protocol - карьера, IT, успех
@chad_protocol · 12,403
#55
Библиотека задач по Data Science | тесты, код, задания
@ds_problems_lib · 3,967
#56
karpov.courses
@KarpovCourses · 27,313
#57
Время Валеры
@cryptovalerii · 32,080
#58
Математика Дата саентиста
@data_math · 14,427
#59
эйай ньюз
@ai_newz · 98,339
#60
DeepSchool
@deep_school · 10,736
#61
Сиолошная
@seeallochnaya · 81,254
#62
ФКН: Вакансии
@vacancy_cs · 18,458
#63
Yandex for ML
@yandexforml · 19,155
#64
еба́ные идеи для резерча
@ebaresearch · 5,368
#65
Техножрица 👩‍💻👩‍🏫👩‍🔧
@tech_priestess · 15,143
#66
Борис опять
@boris_again · 17,955
#67
Старший Авгур
@senior_augur · 8,372
#68
Take Friends to Luna Park
@hrlunapark · 21,014
#69
New Yorko Times
@new_yorko_times · 10,720
#70
LLM под капотом
@llm_under_hood · 30,295
#71
что-то на DL-ском
@nadlskom · 5,152
#72
Поступашки - ШАД, Стажировки и Магистратура
@postypashki_old · 47,236
#73
Жёлтый AI
@zheltyi_ai · 9,375
#74
Kali Novskaya
@rybolos_channel · 19,139
#75
grokaem себя
@grokaem_seby · 2,759
#76
РИСЕРЧОШНАЯ
@researchoshnaya · 2,464
#77
DevOps
@DevOPSitsec · 23,892
#78
Kantor.AI
@kantor_ai · 12,217
#79
Дратути Антон
@blog_toxa · 4,355
#80
ODS Events
@datafest · 8,862
#81
Вадим Новосёлов | Карьера и удалёнка в IT
@gernar228 · 5,694
#82
Reliable ML
@reliable_ml · 6,606
#83
Denis Sexy IT 🤖
@denissexy · 140,845
#84
No Data No Growth | Pavel Bukhtik
@nodatanogrowth · 12,762
#85
Neural Networks | Нейронные сети
@neural · 11,714
#86
Python tests
@python_testit · 6,865
#87
Запрети мне псевдолейблить
@pseudolabeling · 4,507
#88
Пресидский залив
@neural_prosecco · 8,845
#89
Стать специалистом по машинному обучению
@toBeAnMLspecialist · 10,884
#90
Knowledge Accumulator
@knowledge_accumulator · 5,683
#91
Искусственный интеллект. Высокие технологии
@vistehno · 70,132
#92
AIMoLdin Jobs (DSML.KZ)
@ml_jobs_kz · 11,250
#93
Katser
@DataKatser · 2,182
#94
Заметки Computer Vision инженера
@CVML_team · 6,118
#95
DLStories
@dl_stories · 15,547
#96
Душный NLP
@stuffyNLP · 6,718
#97

Read from Telegram’s recommendation API, most recently 24 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Data Science Jobs
@datasciencejobs · 22,621
Telegram ranks this channel #6 of 93 here — alongside 92 others — read 21 September 2026
Job for Analysts & Data Scientists
@foranalysts · 37,857
Telegram ranks this channel #7 of 96 here — alongside 95 others — read 1 September 2026
Machine learning Interview
@machinelearning_interview · 30,562
Telegram ranks this channel #9 of 98 here — alongside 97 others — read 7 September 2026
Анализ данных (Data analysis)
@data_analysis_ml · 51,973
Telegram ranks this channel #11 of 93 here — alongside 92 others — read 25 August 2026
Data Science. SQL hub
@sqlhub · 36,003
Telegram ranks this channel #13 of 87 here — alongside 86 others — read 2 September 2026
Python вопросы с собеседований
@python_job_interview · 24,885
Telegram ranks this channel #14 of 90 here — alongside 89 others — read 15 September 2026
Data Science
@datascienceiot · 42,462
Telegram ranks this channel #15 of 76 here — alongside 75 others — read 29 August 2026
Data Science | Machinelearning [ru]
@devsp · 19,651
Telegram ranks this channel #16 of 91 here — alongside 90 others — read 30 September 2026
Python/ django
@pythonl · 58,245
Telegram ranks this channel #22 of 84 here — alongside 83 others — read 22 August 2026
Dev & ML Connectable Jobs
@dev_connectablejobs · 29,105
Telegram ranks this channel #24 of 94 here — alongside 93 others — read 10 September 2026
Machinelearning
@ai_machinelearning_big_data · 275,343
Telegram ranks this channel #24 of 95 here — alongside 94 others — read 10 August 2026
Python Job | Вакансии | Стажировки
@job_python · 23,474
Telegram ranks this channel #36 of 96 here — alongside 95 others — read 19 September 2026
Remote Junior (INFLOW)
@remotejun · 26,834
Telegram ranks this channel #44 of 98 here — alongside 97 others — read 12 September 2026
Young & Junior - вакансии IT
@young_june · 79,307
Telegram ranks this channel #49 of 99 here — alongside 98 others — read 20 August 2026
Data Secrets
@data_secrets · 96,159
Telegram ranks this channel #56 of 98 here — alongside 97 others — read 17 August 2026
karpov.courses
@KarpovCourses · 27,313
Telegram ranks this channel #63 of 96 here — alongside 95 others — read 10 September 2026
DevOps
@DevOPSitsec · 23,892
Telegram ranks this channel #66 of 90 here — alongside 89 others — read 18 September 2026
Relocate.Me: Jobs & Moving Abroad
@relocateme · 34,733
Telegram ranks this channel #68 of 89 here — alongside 88 others — read 3 September 2026
Искусственный интеллект. Высокие технологии
@vistehno · 70,132
Telegram ranks this channel #72 of 94 here — alongside 93 others — read 20 August 2026
DataFlair
@dataflair · 18,577
Telegram ranks this channel #81 of 83 here — alongside 82 others — read 4 October 2026
Take Friends to Luna Park
@hrlunapark · 21,014
Telegram ranks this channel #83 of 88 here — alongside 87 others — read 28 September 2026
Yandex for ML
@yandexforml · 19,155
Telegram ranks this channel #90 of 96 here — alongside 95 others — read 4 October 2026
Stepik – онлайн-курсы
@stepik_courses · 28,865
Telegram ranks this channel #92 of 93 here — alongside 92 others — read 16 September 2026

This channel appears in 23 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 12 November 2026 — this entry's latest reading, not the date you are reading this.

“Data Science Jobs” (@datascienceml_jobs), 21,640 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/datascienceml_jobs.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.