Jess's unfair advantage is a deep niche and a real conversation
Most creators chase reach. Jess chased a narrow audience of data people and got them talking, not just scrolling.
Jess Ramos is an ex-corporate data analyst and data scientist who got fired from her tech job, went all in on LinkedIn, and turned it into Big Data Energy, a full-time data and AI media business. She is a LinkedIn Top Voice and LinkedIn Learning instructor, and her feed is not a stream of generic motivation. It is a running masterclass for one specific audience: data and AI practitioners trying to break in, level up, or stay relevant. She teaches SQL, tells the truth about the job market, and narrates her own journey, all in the same unmistakable voice.
Her numbers look modest until you read the right one. Across 100 posts she averages 251 reactions, which is small next to the milestone-led mega-accounts. But niche-authority growth is when you win a narrow, high-value audience so completely that engagement depth, not raw reach, becomes your moat. Jess's comment-to-reaction ratio is 18.7%, roughly three times the LinkedIn norm of about 6%. Nearly one comment for every five reactions. That is not a broadcast. That is a community.
Broad, generic posts that rack up likes from people who will never buy, hire, or partner. Big numbers, thin audience.
A narrow audience of data and AI practitioners who comment, save, and repost. Smaller reach, far deeper trust.
“I make recruiters BEG to hire me. Not because I got lucky, but because I made LinkedIn work FOR me.”
— From her post on the 3 things she does daily on LinkedIn (461 reactions)
Five findings that repeated across 100 posts
- Depth beats reach. She averages 251 reactions but a 18.7% comment-to-reaction ratio, about 3x the platform norm. The account is a conversation, not a megaphone.
- SQL is the anchor. Her single biggest post, 'There are only 3 levels of SQL' (888 reactions), is a teaching post. Owning one narrow skill is what built the audience.
- The journey is the emotional payload. Getting fired, speaking at Cannes, retiring her husband, all told in the first person, full-circle.
- Integrity is the product. She publicly walked away from a $7,000 brand deal over an AI safety failure, and the trust that built is why brands pay her at all.
- Near-daily discipline. About 9.7 posts a week, heaviest on Thursday and Monday, for over four years straight.
The numbers behind the account
The headline is not her reach, it is her comment ratio: nearly triple the LinkedIn norm, on a near-daily cadence.
Start with the one number that reframes everything else. On LinkedIn, a healthy comment-to-reaction ratio sits around 6%. Jess runs at 18.7%, roughly three times that. She averages 251 reactions and 47 comments per post, so almost one in five people who react also stop to write something. For a niche educator, that depth is worth more than a viral post nobody remembers, because a commenter is a relationship and a relationship is a customer, a hire, or a brand partner.
The reach comes from volume and consistency. She posts about 9.7 times a week, near-daily and often twice a day, concentrated on weekdays. That midweek-and-Monday rhythm lines up with how the platform distributes B2B content, which we break down in our guide to how the LinkedIn algorithm works.
When she posts
The content-type mix
Where the engagement comes from
The top posts
| # | Post | Reactions | Comments | Reposts |
|---|---|---|---|---|
| 1 | 'There are only 3 levels of SQL' | 888 | 70 | 60 |
| 2 | 'The data analyst role is fundamentally changing' (sponsored) | 839 | 48 | 35 |
| 3 | 'I went to a live DJ set built with AI' (sponsored) | 771 | 110 | 43 |
| 4 | Landing her dream speaking gig at Cannes | 761 | 170 | 8 |
| 5 | 'Data professionals spend 80% of their time cleaning data' | 737 | 75 | 87 |
| 6 | Speaking with LinkedIn at Cannes | 723 | 111 | 12 |
Her top teaching post cleared 888 reactions while the median post sits at 191, so the tiered SQL breakdowns clearly outrun the average. Want to see how your own account stacks up on cadence and comment depth? Run it through our free LinkedIn analyzer.
The six content pillars
Every post is one of six repeatable buckets, so a niche educator never runs out of things to say.
Tiered, save-worthy lessons on SQL, data cleaning, and Python that anchor the whole niche.
How to break in, level up, spot a firing, and negotiate, from someone who did it publicly.
Cannes, Jeff Bezos, keynotes, all told first-person and full-circle from the firing.
Sponsored deep-dives that teach something real, always disclosed, never a cookie-cutter ad.
One repeated argument: your AI is only as good as the messy data layer underneath it.
The hard, unglamorous truth, from a $7,000 walkaway to the crying behind a raise.
Pillar 1: SQL and data-skill teaching (the reach engine)
Why it works: Her single biggest post is a teaching post with a tiered structure. 'There are only 3 levels' makes an intimidating skill feel mappable, and tying level 3 to a real salary ($153K) gives the lesson stakes. Own one narrow skill and teach it in tiers.
Pillar 2: Data-career strategy (the audience magnet)
Why it works: Career-strategy posts pull her exact audience (people worried about their data jobs) and pull the most comments. Note the middle tactic is 'engage in comments', which is literally the behavior driving her 18.7% ratio. She teaches the loop she runs.
Pillar 3: Milestones and the journey (the emotional payload)
Why it works: The milestone is only half the post. The other half is the origin story, fired from corporate, retired her husband, four years of showing up. Milestone plus journey earns her single highest comment count (170), because people invest in the arc, not the award.
Pillar 4: Brand partnerships, her way (the business)
Why it works: This is her monetization engine and her second-biggest post overall, and it opens with '#Sponsored'. The deal still teaches a real trend ('agentic architect') in her own voice, so the ad earns reach instead of repelling it. Disclosed plus useful is the whole trick.
Pillar 5: The data-foundation thesis (the point of view)
Why it works: One argument, repeated in a dozen forms: the shiny AI model matters less than the messy data layer beneath it. A single recurring thesis gives a busy feed a spine, so every post reinforces the same expertise instead of scattering it.
Pillar 6: Radical honesty and integrity (the trust engine)
Why it works: Publicly turning down money is the strongest trust signal a creator has, and it drew 115 comments. For an account that runs on brand deals, visible integrity is not a side note, it is the product: it is why her audience believes the deals she does take.
The hooks that earned the comment
Her openers are concrete and first-person: a hard number, a myth, or a confession. She never warms up.
Bound an intimidating skill. 'There are only 3 levels of SQL.'
Open on a surprising figure. 'Data professionals spend 80% of their time cleaning data.'
Flip conventional wisdom. 'Most SQL tutorials are designed to make you feel dumb.'
Lead with the win, then the arc. 'I landed my DREAM speaking gig at Cannes.'
Say the hard thing plainly. 'I walked away from a $7,000 brand deal.'
Before and after, with numbers. 'In 11 months, I negotiated $71K to $153K.'
For the mechanics of writing openers like these, our guide to writing LinkedIn hooks goes deeper, and you can pressure-test your own first line in the free hook generator.
Her top hooks, by the numbers
| Hook type | Opening line | Reactions |
|---|---|---|
| Number or tier hook | 'There are only 3 levels of SQL.' | 888 |
| Milestone reveal | 'I landed my DREAM speaking gig at Cannes.' | 761 |
| Stat drop | 'Data professionals spend 80% of their time cleaning data.' | 737 |
| Vulnerable confession | 'I walked away from a $7,000 brand deal.' | 313 |
A voice that sounds like a text from a smart friend
High energy, first person, all caps for emphasis, and a hard rule: disclose everything and stay concrete.
- Writes in the first person 'I', always. It is her story, her salary, her opinion.
- Uses the ↳ arrow to turn any lesson into a scannable, save-worthy list.
- Emphasizes with CAPS and emoji, not corporate adjectives. Energy over polish.
- Anchors every claim to a real number: $153K, $71K, $7,000, four years.
- Closes teaching posts with a plain ask: 'Repost for your network and save for later.'
- Discloses every partnership openly with #Sponsored or a partner tag, no exceptions.
The voice is recognizable partly through signatures: the Big Data Energy brand and its ⚡ glyph, the sarcastic setup ('Posting on LinkedIn is probably a waste of time...'), and a habit of following any brag with the messy backstory. She teaches the same visual formats she posts, and if you want to build one, our guide to making a LinkedIn carousel walks through it.
What she does, and doesn't, do
- Write in the first person
- Anchor claims to real numbers
- Disclose every partnership plainly
- Teach one narrow skill relentlessly
- Show the messy backstory
- Hide behind a corporate 'we'
- Make vague, unmeasurable claims
- Disguise ads as organic posts
- Chase every trending topic
- Present only the highlight reel
Holding that voice across teaching, career advice, milestones, and disclosed brand deals at nearly ten posts a week is the part almost nobody sustains, and it is exactly the gap CaptureFlow closes. CaptureFlow is an AI content agent that turns your expertise into weeks of on-brand content for every platform. You capture one idea in 5 minutes (a voice note, a screen recording of a query, a moment at a conference), and CaptureFlow, trained on your voice and past posts, drafts native content for each channel, a LinkedIn post, an X thread, a carousel, a short video, so a data creator can hold the cadence without burning out. See how the AI content agent works, or how it fits the way creators build a business.
The systems underneath the posts
A funnel and a flywheel quietly turn free SQL lessons into brand deals, courses, and speaking gigs.
The niche-authority funnel
Her audience is her product. Because it is a narrow, high-value niche, brands like IBM, Microsoft, and Tableau pay premium rates to reach it, which is only possible because the free teaching built the trust first.
The trust-to-partnership flywheel
- 1Teach a data skill for freeA tiered SQL lesson, a data-cleaning breakdown, a career truth.
- 2The community engagesComments and DMs, at three times the platform norm.
- 3Authority compoundsTop Voice status, keynote invites, a recognizable niche brand.
- 4Brands pay to reach the nicheDisclosed, useful sponsored deep-dives in her own voice.
- 5The sponsored trip becomes contentCannes and Microsoft Build turn into milestone posts, and back to teaching.
Choosing the media
A carousel or image graphic built to be saved and reposted.
A short talking-head video, her highest-volume format.
A real photo from the event, the highest-reacting format.
An interview or on-the-ground video, always disclosed.
Plain text. The honesty carries it with no visual needed.
Text or video, structured with ↳ arrows to be scannable.
This niche-educator model is the close cousin of the one we mapped in the Allie K. Miller playbook, where deep expertise, not company milestones, is the engine. For any creator building a business on one narrow skill, Jess is the template: teach relentlessly, get the room talking, and let the trust do the selling.
Your 30-day challenge
Run the playbook for a month. Pick one narrow skill, teach it relentlessly, and get your audience talking.
- Days 1-2: Name the one narrow skill you will become known for
- Days 3-4: Post a tiered teaching lesson ('There are only N levels of X')
- Days 5-7: Reply to every comment yourself to seed the conversation
- Days 8-9: Share an origin-story milestone, the win plus the messy backstory
- Days 10-11: Post a career truth your exact audience is worried about
- Days 12-14: Drop a stat-based hook with a real number in the first line
- Days 15-17: State your one recurring thesis as plainly as you can
- Days 18-19: Publish a vulnerable, honest post with no highlight-reel gloss
- Days 20-21: Post a save-worthy carousel or checklist for your skill
- Days 22-24: Turn a real event or moment into a photo milestone post
- Days 25-27: Repackage your best teaching post in a new format
- Days 28-30: Review which posts drove comments and double down
Want the near-daily cadence without writing every post from scratch? That is exactly what CaptureFlow's content agent automates, and you can see the plans on our pricing page.
The metrics to track weekly
| Metric | Benchmark to aim for |
|---|---|
| Comment-to-reaction ratio | 10%+ (Jess runs 18.7%) |
| Comments per post | 40+ |
| Reactions per post | 200+ |
| Weekday posting cadence | 5+ per week |
| Saves and reposts on teaching posts | Trending up |
| Replies you write yourself | Every comment, week one |
The takeaways
- 01Optimize for comments, not reach. Jess's 18.7% comment-to-reaction ratio is about 3x the LinkedIn norm, and it is her real moat.
- 02Own one narrow skill. Her biggest post ('There are only 3 levels of SQL', 888 reactions) is a teaching post, not a hot take.
- 03Bound the hard stuff. Tiered hooks like '3 levels' and stat hooks like '80%' make an intimidating skill feel learnable.
- 04Show the whole journey. Milestones land because she attaches the origin story: fired, four years in, full-circle.
- 05Make integrity visible. Publicly walking away from a $7,000 brand deal is why the deals she takes are believed.
- 06Post near-daily on weekdays, and batch-capture so a ten-a-week cadence survives a busy week.
Frequently asked questions
- How did Jess Ramos grow her LinkedIn following?
- By teaching one narrow skill, SQL and data analysis, relentlessly to a niche audience of data and AI practitioners, and by engaging in the comments herself. Across 100 recent posts she averaged 251 reactions but a 18.7% comment-to-reaction ratio, about three times the platform norm, on a near-daily cadence.
- What kind of post performs best for Jess Ramos?
- Tiered teaching posts and journey milestones. Her top post, 'There are only 3 levels of SQL', earned 888 reactions, and her Cannes speaking milestone earned 761 reactions with 170 comments.
- How often does Jess Ramos post, and when?
- About 9.7 times a week, near-daily and often twice a day, concentrated on weekdays with Thursday and Monday heaviest and weekends lighter.
- How do you apply this playbook without spending hours a week?
- Batch-capture your real expertise, a query, a lesson, a moment, then let a content agent draft in your voice. CaptureFlow turns one 5-minute capture into a week of native posts across platforms, so you can hold a near-daily cadence without writing every post from scratch.
