Find a post in r/datascience

Ranked over every collected post title and body in this community. The corpus chunk is fetched once, then searched entirely in your browser — nothing you type leaves this page.

Type a phrase to rank every collected post in this community.

Top-content observatory · Ranked archive + recent pool

What rises in r/datascience.

312 ranked historical records · 1,000 inferred recent candidatesStudy what became prominent, what persists, and what is currently breaking through. This archive is not a census of all subreddit activity.

Historical canon312

Older ranked records represented before 2022-08-23. Useful for prominence and memory—not total activity.

Recent candidate pool1,000

Newest records from 2022-08-23 to 2026-08-07. The boundary is inferred because original retrieval provenance was not stored.

Analysis availability · Limited history

Recent-pool signals remain useful, but only 312 canon records limit long-range interpretation. Topic comparison is withheld because this corpus has not been topic-enriched.

Historical material available

312 ranked historical records span 6 represented years. Topic evolution is not shown until this corpus has enriched topic assignments.

6represented years

Recent contenders

What earned attention in this snapshot.

Age bands are measured as of 2026-08-07, not today. The newest-post pool is filtered within those bands, then ranked by score and reply-count percentiles. Posts newer than 7 days are withheld when enough mature candidates exist.

Why is it that stakeholders expect ML models to have 0% error rate?Unclassified · 7–13 days old at snapshot · 372 score · 108 replies

100index02

Data Science Has Become a Pseudo-ScienceUnclassified · 60+ days old at snapshot · 2,760 score · 351 replies

99index03

Why do new analysts often ignore R?Unclassified · 60+ days old at snapshot · 2,479 score · 286 replies

99index04

All these layoffs have made me question my job searchUnclassified · 14–29 days old at snapshot · 203 score · 73 replies

99index05

Are all data science jobs just Gen AI now?Unclassified · 30–59 days old at snapshot · 331 score · 135 replies

98index06

Here are the questions I was asked for my entry level DS job!Unclassified · 60+ days old at snapshot · 1,572 score · 254 replies

97index07

Data scientist quits her job at SpotifyUnclassified · 60+ days old at snapshot · 1,393 score · 363 replies

97index08

Friendly reminder not to work too hard. You'll just get firedUnclassified · 60+ days old at snapshot · 1,707 score · 202 replies

97index09

My Data Science Manifesto from a Self Taught Data ScientistUnclassified · 60+ days old at snapshot · 2,073 score · 175 replies

97index10

Thoughts?Unclassified · 60+ days old at snapshot · 1,727 score · 187 replies

97index11

I am a staff data scientist at a big tech company -- AMAUnclassified · 60+ days old at snapshot · 1,225 score · 424 replies

97index12

MIT report: 95% of generative AI pilots at companies are failingUnclassified · 60+ days old at snapshot · 2,305 score · 152 replies

97index

Candidate index is relative to this recent pool, not a prediction of future quality or final Reddit rank.

Candidate-pool signals

Read the recent pool without contaminating the canon.

Every lens below uses only the inferred newest-post cohort from 2022-08-23 onward. They describe patterns inside that selected pool—not subreddit-wide prevalence.

Swipe or scroll horizontally to see all signal values.

Repetition

What the community keeps saying

Distinct-post frequency across 1,000 titles and 798 available bodies. High-information two-word frames lead; normalized domain terms remain expandable.

01data sciencephrase

Peak 100.0 · latest 36.4

281 posts · 28.1%

02data scientistphrase

Peak 50.0 · latest 0.0

128 posts · 12.8%

03job searchphrase

Peak 33.3 · latest 9.1

71 posts · 7.1%

04science fieldphrase

Peak 15.2 · latest 9.1

67 posts · 6.7%

05learning resourcesphrase

Peak 18.2 · latest 9.1

66 posts · 6.6%

06data scientistsphrase

Peak 25.0 · latest 0.0

65 posts · 6.5%

07resources e.gphrase

Peak 50.0 · latest 9.1

65 posts · 6.5%

08e.g booksphrase

Peak 50.0 · latest 9.1

65 posts · 6.5%

Show recurring domain terms

09dataterm

Peak 100.0 · latest 54.5

570 posts · 57.0%

10scienceterm

Peak 100.0 · latest 36.4

290 posts · 29.0%

11jobterm

Peak 66.7 · latest 27.3

243 posts · 24.3%

12workterm

Peak 100.0 · latest 27.3

231 posts · 23.1%

13allterm

Peak 100.0 · latest 18.2

230 posts · 23.0%

14timeterm

Peak 100.0 · latest 36.4

177 posts · 17.7%

15learningterm

Peak 100.0 · latest 9.1

160 posts · 16.0%

16donterm

Peak 100.0 · latest 9.1

158 posts · 15.8%

17modelterm

Peak 100.0 · latest 27.3

146 posts · 14.6%

18questionsterm

Peak 50.0 · latest 18.2

140 posts · 14.0%

Inspect language emerging within the recent pool

Emergence

What started appearing more often

Per-post prevalence in 500 earlier versus 500 later posts · 798 bodies available. Minimum support removes one-off spikes.

01searchterm

Peak 33.3 · latest 9.1

+8.0pp · 5.2% → 13.2%

02answersterm

Peak 20.0 · latest 9.1

+7.0pp · 4.2% → 11.2%

03job searchphrase

Peak 33.3 · latest 9.1

+7.0pp · 3.6% → 10.6%

04topicsterm

Peak 20.0 · latest 9.1

+6.8pp · 4.2% → 11.0%

05tutorialsterm

Peak 15.2 · latest 9.1

+6.6pp · 3.4% → 10.0%

06weeklyterm

Peak 15.2 · latest 9.1

+6.4pp · 3.6% → 10.0%

07learning resourcesphrase

Peak 18.2 · latest 9.1

+6.4pp · 3.4% → 9.8%

08schoolsterm

Peak 15.2 · latest 9.1

+6.4pp · 3.2% → 9.6%

09bootcampsterm

Peak 18.2 · latest 9.1

+6.4pp · 3.2% → 9.6%

10prospectsterm

Peak 15.2 · latest 9.1

+6.4pp · 3.2% → 9.6%

11threadsterm

Peak 15.2 · latest 9.1

+6.4pp · 3.2% → 9.6%

12science fieldphrase

Peak 15.2 · latest 9.1

+6.2pp · 3.6% → 9.8%

Show more emerging patterns

13e.gterm

Peak 50.0 · latest 9.1

+6.2pp · 6.6% → 12.8%

14weekly enteringphrase

Peak 15.2 · latest 9.1

+6.2pp · 3.2% → 9.4%

15entering transitioningphrase

Peak 15.2 · latest 9.1

+6.2pp · 3.2% → 9.4%

16welcome weekphrase

Peak 15.2 · latest 9.1

+6.2pp · 3.2% → 9.4%

17week enteringphrase

Peak 15.2 · latest 9.1

+6.2pp · 3.2% → 9.4%

18thread questionsphrase

Peak 15.2 · latest 9.1

+6.2pp · 3.2% → 9.4%

Language-marker spectrum

Which language markers became more visible

Boundary-aware phrase-marker rates across 1,000 titles and 798 available post bodies. Categories may overlap and describe language patterns—not author emotion.

CuriosityFrustrationUncertaintyExcitementUrgencyAppreciation

View marker dictionary

curiosity: why, how, what, explain, understand, learn, curious, wonder, anyone know, thoughts on

frustration: broken, fails, failed, error, issue, problem, stuck, doesn't work, not working, frustrated, worse, unusable, bug

uncertainty: maybe, might, could, unsure, not sure, uncertain, possibly, seems, apparently, i think

excitement: amazing, awesome, excited, love, can't wait, incredible, finally, great, impressive, game changer, wow

urgency: urgent, asap, right now, immediately, today, deadline, breaking, just released, now available

appreciation: thanks, thank you, appreciate, helpful, grateful, shoutout, well done, great work, kudos

Post-language marker rates by month
Month	Curiosity	Frustration	Uncertainty	Excitement	Urgency	Appreciation
2022-08	25.0%	0.0%	25.0%	0.0%	0.0%	0.0%
2022-09	33.3%	8.3%	8.3%	8.3%	0.0%	25.0%
2022-10	30.0%	0.0%	10.0%	10.0%	0.0%	0.0%
2022-11	25.0%	0.0%	25.0%	0.0%	0.0%	0.0%
2022-12	0.0%	0.0%	11.1%	0.0%	0.0%	0.0%
2023-01	28.6%	0.0%	14.3%	14.3%	0.0%	0.0%
2023-02	33.3%	0.0%	0.0%	0.0%	0.0%	16.7%
2023-03	42.9%	0.0%	14.3%	57.1%	0.0%	0.0%
2023-04	40.0%	0.0%	0.0%	40.0%	0.0%	0.0%
2023-05	50.0%	0.0%	25.0%	25.0%	0.0%	25.0%
2023-06	100.0%	0.0%	100.0%	0.0%	0.0%	0.0%
2023-07	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
2023-08	20.0%	20.0%	20.0%	20.0%	0.0%	20.0%
2023-09	50.0%	0.0%	50.0%	16.7%	0.0%	0.0%
2023-10	80.0%	20.0%	40.0%	0.0%	20.0%	0.0%
2023-11	60.0%	0.0%	20.0%	0.0%	20.0%	0.0%
2023-12	100.0%	0.0%	0.0%	0.0%	0.0%	0.0%
2024-01	28.6%	28.6%	0.0%	14.3%	14.3%	0.0%
2024-02	75.0%	0.0%	25.0%	0.0%	0.0%	0.0%
2024-03	20.0%	0.0%	40.0%	20.0%	20.0%	20.0%
2024-04	60.0%	0.0%	20.0%	0.0%	0.0%	0.0%
2024-05	60.0%	0.0%	40.0%	0.0%	0.0%	20.0%
2024-06	100.0%	0.0%	100.0%	100.0%	0.0%	0.0%
2024-07	50.0%	50.0%	0.0%	0.0%	0.0%	0.0%
2024-08	50.0%	0.0%	0.0%	0.0%	0.0%	0.0%
2024-09	60.0%	0.0%	20.0%	0.0%	0.0%	0.0%
2024-10	75.0%	0.0%	25.0%	25.0%	0.0%	0.0%
2024-11	33.3%	0.0%	0.0%	0.0%	0.0%	0.0%
2024-12	60.0%	0.0%	20.0%	0.0%	0.0%	0.0%
2025-01	61.5%	0.0%	15.4%	30.8%	0.0%	23.1%
2025-02	50.0%	25.0%	37.5%	12.5%	0.0%	0.0%
2025-03	73.3%	13.3%	26.7%	26.7%	0.0%	20.0%
2025-04	71.4%	14.3%	28.6%	19.0%	19.0%	42.9%
2025-05	77.4%	9.4%	24.5%	30.2%	9.4%	20.8%
2025-06	73.4%	16.0%	31.9%	22.3%	8.5%	19.1%
2025-07	74.0%	16.9%	31.2%	18.2%	3.9%	14.3%
2025-08	75.0%	16.7%	26.7%	16.7%	13.3%	13.3%
2025-09	60.0%	10.0%	26.7%	18.3%	1.7%	21.7%
2025-10	84.6%	12.8%	30.8%	25.6%	10.3%	23.1%
2025-11	72.0%	10.0%	16.0%	18.0%	0.0%	10.0%
2025-12	51.1%	8.5%	14.9%	21.3%	6.4%	4.3%
2026-01	66.7%	15.4%	20.5%	10.3%	2.6%	10.3%
2026-02	60.0%	12.5%	12.5%	15.0%	10.0%	7.5%
2026-03	75.8%	12.1%	27.3%	3.0%	9.1%	18.2%
2026-04	68.9%	17.8%	17.8%	8.9%	8.9%	6.7%
2026-05	60.9%	17.2%	26.6%	12.5%	3.1%	6.3%
2026-06	61.0%	22.0%	22.0%	9.8%	2.4%	4.9%
2026-07	64.0%	14.0%	30.0%	16.0%	18.0%	2.0%
2026-08	100.0%	27.3%	27.3%	0.0%	9.1%	0.0%

Candidate response distribution

Where recent platform attention accumulated

Posts in the inferred recent candidate pool are binned by Reddit score and upvote ratio. Brighter cells contain more selected posts; score uses a logarithmic scale.

1,000 recent candidates represented · relative platform response, not quality or subreddit-wide reach.

Non-empty recent candidate score and approval density bins
Score band	Upvote-ratio band	Posts
0–0	0–10%	1
0–0	10–20%	4
0–0	20–30%	15
0–0	30–40%	25
0–0	40–50%	27
0–0	50–60%	7
1–1	50–60%	10
1–2	50–60%	5
2–3	50–60%	3
3–5	50–60%	3
5–7	50–60%	1
1–1	60–70%	5
1–2	60–70%	10
2–3	60–70%	7
3–5	60–70%	3
5–7	60–70%	5
7–9	60–70%	8
9–13	60–70%	3
13–18	60–70%	3
18–24	60–70%	2
24–32	60–70%	1
32–44	60–70%	1
1–2	70–80%	4
2–3	70–80%	3
3–5	70–80%	5
5–7	70–80%	10
7–9	70–80%	17
9–13	70–80%	8
13–18	70–80%	11
18–24	70–80%	15
24–32	70–80%	8
32–44	70–80%	7
44–59	70–80%	6
59–79	70–80%	3
79–107	70–80%	1
107–143	70–80%	1
143–193	70–80%	1
465–623	70–80%	1
835–1,119	70–80%	1
2–3	80–90%	1
3–5	80–90%	8
5–7	80–90%	13
7–9	80–90%	11
9–13	80–90%	24
13–18	80–90%	14
18–24	80–90%	27
24–32	80–90%	23
32–44	80–90%	19
44–59	80–90%	14
59–79	80–90%	14
79–107	80–90%	14
107–143	80–90%	7
143–193	80–90%	4
193–258	80–90%	3
258–346	80–90%	3
346–465	80–90%	1
465–623	80–90%	8
623–835	80–90%	4
835–1,119	80–90%	8
1–1	90–100%	2
1–2	90–100%	2
2–3	90–100%	3
3–5	90–100%	3
5–7	90–100%	3
7–9	90–100%	27
9–13	90–100%	14
13–18	90–100%	17
18–24	90–100%	22
24–32	90–100%	21
32–44	90–100%	30
44–59	90–100%	35
59–79	90–100%	38
79–107	90–100%	45
107–143	90–100%	25
143–193	90–100%	24
193–258	90–100%	23
258–346	90–100%	18
346–465	90–100%	11
465–623	90–100%	59
623–835	90–100%	29
835–1,119	90–100%	32
1,119–1,499	90–100%	19
1,499–2,009	90–100%	14
2,009–2,692	90–100%	8
2,692–3,607	90–100%	5

Sources

Inspect available source posts.

Open the posts behind the interpretation. The score distribution is a diagnostic of this selected source set—not a model of the subreddit as a whole.

Inspect collected-score distribution

How attention is distributed

Collected posts grouped into Reddit score bands.

079

1-9172

10-49294

50-99134

100-499181

500-999304

1k-2k109

2k-5k39

5k+0

Available posts by Reddit score

20 available

01data siens4,113 score · 2020-12-07↗02The pain and excitement3,909 score · 2021-07-05↗03Shout Out to All the Mediocre Data Scientists Out There3,624 score · 2020-07-10↗04Let's keep this on...3,607 score · 2022-09-14↗05Guys, we’ve been doing it wrong this whole time3,462 score · 2022-03-21↗06It’s never too early3,409 score · 2020-03-10↗07how about that data integrity yo3,328 score · 2021-07-12↗08Didn’t have to chart this one 🔥3,310 score · 2022-09-20↗09Wait until you see the data in hospitals...3,255 score · 2022-08-15↗10Imposter Syndrome is a problem for me and I think this is the main contributor3,212 score · 2019-12-05↗11How to avoid 1/2-assed data analysis3,179 score · 2024-09-02↗12DS at a glance2,915 score · 2019-11-10↗

Sampling and methodology

Collected records: 1,312

Represented range: 2017-09-19 → 2026-08-07

The corpus combines a broad newest-post listing with bounded top/year and top/all listings. The interface infers the recent boundary from the newest 1,000 records because original retrieval provenance was not stored.

Older records are analyzed as a ranked historical canon. They can show what was prominent and repeatedly surfaced within ranked retrieval; they cannot estimate total monthly activity, publishing habits, or whole-conversation prevalence.

Recent contender ranking compares posts within age bands using score and reply-count percentiles. Platform attention is not evidence quality, accuracy, representativeness, or future performance.

Find a post in r/datascience

What rises in r/datascience.

Historical material available

What earned attention in this snapshot.

Read the recent pool without contaminating the canon.

What the community keeps saying

What started appearing more often

Which language markers became more visible

Which formats carry the conversation—and when

Where recent platform attention accumulated

Inspect available source posts.

How attention is distributed

Available posts by Reddit score