Entry-Level Data & AI Jobs in the US: How to Get Hired in 2026

You want a data or AI job in 2026 and your resume has almost nothing on it. That is the normal starting position, and the market is workable if you aim correctly.

What the current numbers actually show#

JobRise's live feed had 519 open Data & AI listings in the United States on 14 October 2026. Of those, 305 were posted in the last 30 days and 147 in the last 7 days. You can browse the current set on the data jobs hub.

For wider context, the country had 13,720 open listings across all categories, with 8,471 posted in the last 30 days, per the United States hiring report.

One number matters more than the rest for you. Only 2 of those 519 listings look entry-level by title: "AI Research Engineer, New PhD Graduate" at Duolingo, and "Junior Quant - PM Analytics" at Man Group. Both want credentials most applicants do not have.

That is the blunt reality. Companies hiring in this slice are mostly hiring people who already do the work.

Who is hiring and where#

The companies with the most open listings in this snapshot were Anthropic (65), Scaleai (36), Faire (19), Lyft (18), Datadog (18), Pinterest (18), Figma (17), Airbnb (16), Klaviyo (16), and Brex (13). Some of these names are recruiters or staffing firms, so read the listing carefully to know who signs your paycheck.

Cities concentrate hard: San Francisco (175), New York (105), Boston (25), Seattle (9), Denver (8). Full-time roles dominate at 514, with 4 part-time and 1 contract.

If you live outside those five metros, remote roles exist but you compete against a national pool. Local still helps.

The titles you should actually target#

"Junior" and "intern" are rare words in this feed. The work you want hides behind mid-level titles that stretch downward when nobody senior applies. Look at these real listings: "Business Intelligence Analyst" at Carrot, "Data Analyst" at Spectrum Comm Inc, "Policy Development, Technical AI Governance" at Anthropic.

Compare them to the ones you should skip: "Senior Data Scientist, Audio" at Deepgram, "Member of Technical Staff - Post-training (Data Infrastructure)" at Cohere, "Private Markets Secondary Data & AI Vice President" at Neuberger Berman, "Senior Director of Real Estate Financial Modeling and Capital Analytics" at Harmony Homes, "AI Business Transformation Lead" at City Wide Facility Solutions.

Those senior and lead roles are not yours yet. Stop spending evenings rewriting your resume for them.

What pay looks like#

Only 15 of 519 listings in this snapshot showed a salary. What they show skews senior: "Machine Learning Engineer" at Ramp listed $200K, $330K with equity, "AI Solutions Strategist" at Ramp listed $170K, $230K, "Technical Program Manager, AI Delivery" at Cohere listed $140K, $220K with multiple ranges. Lower in the range, "Senior Analyst, Employee Lifecycle Data (Workday)" at Ramp listed $90K, $120K.

Treat these as posted ranges on a specific date, not promises. Actual offers vary by location, level, and negotiation, so verify current figures on the official company careers page before you plan around a number.

Skills employers in this feed expect#

You do not need every tool on a wishlist. You need proof you can finish something. The recurring expectations across these listings are SQL, Python, one dashboarding tool, and clear written communication.

For AI-adjacent roles, add one model API you have actually called, plus basic evaluation thinking: how do you know an output is good enough?

• Write SQL joins and window functions without looking them up
• Clean messy CSVs in pandas and explain what you dropped
• Build one dashboard in Tableau, Power BI, or Looker
• Ship one project that calls an LLM API and stores results
• Write a short README explaining your choices and limits
• Practice explaining a metric tradeoff out loud in two minutes
• Record versions of your work on GitHub with real commit history

A resume bullet you can steal#

Most zero-experience bullets describe coursework. Rewrite them to describe outcomes and tools.

Before: "Responsible for analyzing sales data as part of university business analytics class."

After: "Built a Python and SQL pipeline that cleaned 18 months of messy retail sales data from three source files, found a 12% gap between recorded and shipped units, and presented the fix to a four-person class team in a 10-minute walkthrough."

That second version names the tools, the scale, the finding, and the communication. It survives a recruiter's six-second scan. If you want more help phrasing your own version, the resume builder walks through the structure.

Where entry-level openings actually appear#

Job boards like this one are the fast channel, but they are not the only one. Many junior roles get filled before the listing goes wide.

• University alumni Slack groups and Discord servers
• Company career pages, checked weekly, not daily
• Open source repos where maintainers hire contributors
• Staffing firms that appear as employers on listings
• Local meetup mailing lists in your city
• LinkedIn posts from hiring managers, not just recruiters

The 7-step plan#

1. Pick one lane: analytics, ML engineering, or AI product. Two lanes at once means two half-efforts.
2. Build two projects that mirror real job titles you saw above, like Business Intelligence Analyst or Data Analyst.
3. Publish both on GitHub with a README, sample data, and a short demo video under three minutes.
4. Rewrite your resume bullets using the pattern above: tool, scale, finding, delivery.
5. Apply to 10 roles a week in cities you can reach, and log every application in a spreadsheet.
6. Reach out to one person at each target company with a specific question about their team's stack.
7. Practice your two-minute project story until you can say it without notes.

Do this for eight weeks before you judge results. Most people quit in week three and blame the market.

FAQ#

How many entry-level data and AI roles were open in the US in October 2026?

In JobRise's 14 October 2026 snapshot, 2 of 519 Data & AI listings in the United States had clearly entry-level titles like intern, junior, or new graduate. That is a snapshot of one feed on one day, not a market-wide count.

Do I need a master's degree or PhD to break in?

The two entry-level listings in this snapshot, at Duolingo and Man Group, both imply advanced training. For analyst roles like the ones at Carrot and Spectrum Comm Inc, a bachelor's plus shipped projects usually clears the bar.

Should I apply to senior roles anyway?

Not usually. Senior titles in this feed, such as the Cohere and Deepgram listings, describe work that needs years of production experience. Spend that time on two strong applications instead of twenty weak ones.

What salary should I expect in an entry-level data role?

Posted salaries in this snapshot ranged from $90K at the low end to $330K at the high end, and almost all were senior. Entry-level pay varies widely by city and company, so check the current official posting before assuming a figure.

How long does it typically take to get hired with no experience?

Timelines vary with location, portfolio quality, and how many roles you apply to each week. Plan for a few months of consistent work rather than a few weeks, and keep building while you wait.