How to advertise to data scientists
To advertise to data scientists, be where they read every day: daily.dev Ads, Data Elixir and The Batch, Kaggle and r/datascience. daily.dev gives you a verified company page they follow and puts your posts and releases in the feed of developers who read #data-science and #machine-learning, and in the Data and Databases newsletter, in one plan we run for you.
One plan, built around your company page: we put it in front of data scientists across daily.dev and report on it every week.
Who are the data scientists on daily.dev?
What they read, where it comes from, and what else they follow: the signals a campaign is targeted on.
The tags that reach them
Target any mix; your plan runs the campaign on them.
- #data-science
- #machine-learning
- #python
- #deep-learning
- #statistics
- #pandas
800+ targetable keywords in all (daily.dev Media Kit 2.0, August 2026 — targeting).
Where data scientists get their news
The sources that publish most on these tags, ranked by followers on daily.dev.
- 1
freeCodeCamp
- 2
Hacker News
- 3
Real Python
- 4
Hackaday
- 5
Fireship - 6
ByteByteGo
What they also read
Tags on the same recent posts, as a share of them. Worth adding to a campaign.
- #llm11%
- #data-analysis8%
- #r6%
- #ai-agents4%
- #numpy4%
- #pytorch3%
Tags, sources and co-reading: daily.dev public API snapshot.
How do you reach data scientists?
Developers are the audience that taught the industry to block ads. The way in is not a louder interruption; it is the reading they chose, in the place they open every day. That is why daily.dev Ads exists: to help brands earn a place in that reading, week after week.
- 13K+
- companies whose developers read daily.dev
- 800+
- targetable stacks and topics
- 2,000+
- content sources in the feed
Written by the daily.dev Ads team, which plans and runs every campaign on the platform. Sources on the audience overview.
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The notebook is the post.
Data scientists evaluate a tool by running it on data they know. Publish notebooks they can open and execute on a public dataset; a product tour is closed before the first cell.
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Show the result against the baseline they already have.
This audience compares everything with what it used last week. Put the metric, the baseline and the dataset in the post, so the improvement is specific enough to check.
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They read in Python and adopt in Python.
Lead with the import and the first call, and make sure the example runs in a plain notebook before any platform account exists. That is the post that gets shared with the team.
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Statistics readers distrust a round number.
A claim of accuracy or speed without a confidence interval or a test setup reads as marketing to a statistician. State how the number was measured; that line is what makes it believable.
“The biggest standout was the engagement quality. That’s the kind of result that gets attention internally, because it suggests the message is landing with the right audience.”
Why do developers pay attention on daily.dev?
Nimrod on why marketing to developers is anything but marketing: what developers trust, what they tune out, and how daily.dev was built around it.
More from the team: the developer marketing series →
What do data scientists read, and what should your brand say?
A few things they read and discuss
Examples of popular posts on these tags that data scientists read and talk about on daily.dev. Open any of them to join the conversation.
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Colab is now part of your Google AI plan
Google Developers 3 40
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Hands-On Evolution of Deep Learning – Geoffrey Hinton’s AI Legacy
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Singapore’s government creates a dating app
The Register 1 7
Each post opens on daily.dev with its discussion.
What that means for your message
Your takeaways from what they discuss. Our team writes the creative with you.
- From notebook to production Publish the same model served, with the latency it got
- Data quality Share the bad rows your tool caught on a real dataset, counted
- Compute cost Post training time and GPU hours side by side, with the setup
How do you target data scientists on daily.dev?
Targeting is built on what developers read on daily.dev, not a self-declared profile. You set it once with your campaign manager; your plan runs it, and we optimise it every week.
- Tags
- #data-science, #machine-learning, #python, #deep-learning, #statistics, #pandas, and any of the 800+ targetable keywords
- Seniority
- Junior, mid-level, senior and leadership, from on-platform activity
- Region
- Global, or by region and country
- In your plan
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- Your verified company page
- Your posts in their feed
- The Data and Databases newsletter
- Your logo on the daily.dev homepage
- A weekly report and a campaign manager
- Creative
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Our team works with you to shape, finish and test your creative, so it reads like the posts around it.
Creative specs for every placement
Pick a size
Same work in every size. The size sets your reach.
Explore my options →Prices are quoted per company. See how plans work →
Where else can you reach data scientists?
Where data scientists can be reached with paid media, and what each channel is good at. Most teams combine two or three; a plan here is the always-on part.
| Channel | Format | Target by stack | How you buy | Best for |
|---|---|---|---|---|
 | Your verified company page, your posts in their feed, the newsletter they chose, the homepage | Yes: #data-science, #machine-learning, #python, #pandas, seniority, region | Managed monthly plan | Building a brand developers follow, every week, with creative and reporting done for you |
| Data science newsletters (Data Elixir, The Batch) | One sponsor slot per issue | By list | Per issue | Launch-week spikes |
| Kaggle and Hugging Face communities | Competitions, sponsored datasets and model pages | By competition or model | Sponsorship packages | Hands-on adoption |
| Reddit (r/datascience, r/MachineLearning) | Promoted posts | By subreddit | Self-serve | Discussion and feedback |
| PyData and ODSC | Booths and talks | By event | Sponsorship packages | Community presence |
| Data science podcasts | Host-read sponsorships | By show | Per episode | Brand familiarity |
| LinkedIn Ads | Sponsored posts and message ads | By job title, company and self-declared skills | Self-serve | Reaching managers and buyers by title |
Compare daily.dev with
- Format
- Your verified company page, your posts in their feed, the newsletter they chose, the homepage One sponsor slot per issueCompetitions, sponsored datasets and model pagesPromoted postsBooths and talksHost-read sponsorshipsSponsored posts and message ads
- Target by stack
- Yes: #data-science, #machine-learning, #python, #pandas, seniority, region By listBy competition or modelBy subredditBy eventBy showBy job title, company and self-declared skills
- How you buy
- Managed monthly plan Per issueSponsorship packagesSelf-serveSponsorship packagesPer episodeSelf-serve
- Best for
- Building a brand developers follow, every week, with creative and reporting done for you Launch-week spikesHands-on adoptionDiscussion and feedbackCommunity presenceBrand familiarityReaching managers and buyers by title
Channel facts from each channel's own public pages, October 2026. Prices are not compared.
What do teams build with data scientists on daily.dev?
Build your brand with them
Show up every day in the reading data scientists chose, with your posts, releases and point of view, so yours is the name they know when they pick a tool.
Grow a community around your product
Your verified company page is where data scientists follow you, discuss your posts and come back for your next release.
Strengthen your employer brand
Share engineering stories, culture and open roles with data scientists where they already discover tools and ideas.
Brands building with developers on daily.dev
Brands building with developers on daily.dev
Google, AWS, Google Cloud, Cursor, Vanta, Zoho, Atlassian, Notion, Okta, Sentry, Datadog, JetBrains, Postman, Snyk, ClickHouse, Edge Impulse, RevenueCat, QA Wolf, TigerData, PostHog, LaunchDarkly, Neo4j, Temporal, Sonar, Appwrite, dbt Labs, Retool, Pulumi, CodeRabbit, Windsurf, OpenRouter, Bright Data, Stream, Postmark, Novu, context.dev
Guides on reaching data scientists
- How to market to data scientists
- How to reach data engineers and ML practitioners
- Target developers by programming language: a marketer’s guide
- Tech stack targeting: reaching developers by the tools they use
- Best developer advertising platforms
- Developer marketing platforms compared: the channel mix
All guides: developer marketing resources →
Advertising to data scientists: your questions
Pick a plan. We reach
data scientists for you.
Tell us what you sell and the regions you need. We come back with a plan size, the reach it buys and a quote.
Other audiences: Data engineers AI engineers Python developers All audiences →
