Top Companies Hiring for Data & AI Jobs in New York (Oct 2026)

You keep applying to Data & AI roles in New York and you cannot tell which employers are actually hiring. Career pages say "we're always hiring" and mean nothing by it. Job titles blur together.

Here is a real snapshot. On 14 October 2026, the JobRise live jobs feed (jobrise.io) showed 105 open Data & AI listings in New York, and you can browse them yourself at our Data & AI jobs in New York hub. Of those, 56 were posted in the last 30 days and 22 in the last 7 days. Counts of open listings. Not a market survey.

They move daily.

Who is hiring right now#

Ten employers carry most of the volume. Names are exactly as they appear on the listings, and some of these are recruiters or staffing firms rather than the end employer.

1. Datadog, 15 open listings
2. Anthropic, 11
3. Faire, 10
4. Spotify, 9
5. Ramp, 8
6. Justworks, 7
7. Lyft, 6
8. Scaleai, 5
9. Neuberger Berman, 4
10. Stripe, 4

Titles tell you what the job actually is. Datadog's listings include "Senior Design Manager - AI Monitoring & Management", a management and product-side AI seat rather than a modeling job, and Anthropic's include "Policy Development, Technical AI Governance", which is policy and governance work. Neuberger Berman's four listings sit in private markets data: "Private Markets Secondary Data & AI Vice President", "Private Markets Secondary Data Associate", "Specialist, Account Data Management & Governance", plus one more in that cluster.

Other example titles in the snapshot: "Senior Manager, Data Science and Machine Learning" at Squarespace, "AI Research Engineer, New PhD Graduate" at Duolingo, "Senior Data Scientist" at Justworks. Read before you apply. "Data & AI" is a category, not a job.

How New York compares nationally#

New York holds 105 of the 519 Data & AI listings JobRise showed across the United States on 14 October 2026, and inside the city that category is 105 of 1,165 listings across all categories. So Data & AI is a thin slice of New York hiring overall, yet New York still takes a large share of national Data & AI volume.

That cuts both ways. Concentration here means more recruiters to talk to and more teams within subway distance, but it also means you compete against everyone who moved to New York for exactly this reason. For national context beyond this snapshot, the JobRise Hiring Report: the US tracks listing trends over time.

Apply to other cities too.

What the pay actually shows#

Only 10 of the 105 listings showed a salary. That is normal. Most employers in this category hide pay until late.

Where pay is posted, the spread is wide. Ramp posted five of the visible ranges: "Senior Analyst, Employee Lifecycle Data (Workday)" at $90K to $120K with equity, "Machine Learning Engineer" at $200K to $330K with equity, "AI Solutions Strategist" at $170K to $230K with equity, "Senior Analyst, Economic Research and Special Projects" at $140K to $190K with equity, and "AI Solutions Engineer" at $217K to $298K with equity. Cohere posted "Data Engineer, Data Foundations" at $160K to $325K with equity, multiple ranges.

A $90K floor and a $330K ceiling. Same city. Same category.

Treat posted ranges as a starting point rather than a promise, because the final number depends on level, equity, and how the comp band was built. Verify current figures with the employer directly and check New York's pay transparency rules before you anchor your ask.

Entry-level is nearly invisible#

Only 1 of 105 listings looked entry-level on its title: "AI Research Engineer, New PhD Graduate" at Duolingo. If you are early career, that is the honest picture. New York's Data & AI market right now is hiring experienced people.

Do not read that as "give up." Read it as "adjust your search." Titles like "Associate", "Analyst II", or "Data Operations" sit outside this slice and often take people with 1 to 2 years of experience, and adjacent categories inside that 1,165 total are where juniors actually get hired.

Widen the net.

How to target each employer type#

Product and infrastructure companies like Datadog, Spotify, Lyft, Stripe, and Faire hire data people to work on their own systems. Show a project where your work changed a product decision. Metrics beat adjectives.

AI labs and AI-heavy firms like Anthropic, Scaleai, and Cohere screen for depth, so lead with research, publications, model work, or governance experience that matches the exact title. A generic "passionate about AI" line gets you filtered out. Depth or nothing.

Fintech and financial firms like Ramp, Neuberger Berman, and Justworks care about data quality, controls, and domain knowledge. Speak to lineage, governance, and accuracy. Neuberger Berman's "Specialist, Account Data Management & Governance" is a compliance-adjacent seat, not a modeling one.

Recruiters and staffing firms on the list are a different motion. They place across many clients, so keep the relationship warm, reply fast, and tell them exactly which titles and comp band you will take.

Referral and outreach scripts#

Cold outreach works when it is short and specific. Two scripts you can adapt.

Referral request to someone you know:

Hi Sam, hope you're well. I'm looking at the Senior Data Scientist role at Justworks and I think my work on churn modeling at Acme lines up. Would you be willing to pass my resume along? No worries at all if not. Happy to return the favor.

Cold message to a hiring manager or team lead:

Hi Priya, I saw Datadog is hiring for Senior Design Manager, AI Monitoring & Management. I spent two years leading design for an observability tool where we cut alert noise by about 40%. If the team is still looking, I'd value 15 minutes to hear what you need most in the first six months.

Notice what both do. Name the exact role, give one specific proof point, and ask for something small, because a message that asks for "any advice on breaking in" gets deleted. No paragraph about your career story.

A 7-step plan#

1. Pull the 105 open listings and sort by post date. Apply to the 22 posted in the last 7 days first, since those are the freshest.
2. Pick 5 employers from the ranked list and read every title carefully. Drop any whose work does not match your actual experience.
3. Rewrite your top resume bullet for each target. Mirror the language in the title, not the whole posting.
4. Find two people at each target on LinkedIn. Look for the hiring manager and one peer on the team.
5. Send the referral script to anyone you have a real connection with, then the cold script to the rest. Cap it at two messages per company.
6. Track everything in a spreadsheet: company, role, date applied, contact, last touch. Follow up once after 7 days, then move on.
7. Check the company's background before you invest hours. Our free company insights tool pulls role history, pay signals, and hiring patterns in one place.

Do steps 1 to 3 in one sitting. The rest spreads across two weeks.

FAQ#

Are these numbers current?

They are a dated snapshot taken on 14 October 2026 from the JobRise live jobs feed. Listings close and open daily, so treat the counts as a starting point and re-check the feed before you plan your week.

Should I apply to recruiters or direct employers?

Both. Recruiters multiply your reach across clients, but direct applications to the employer usually move faster and give you more control over which role you land. Do not send the same generic resume to both.

Is $330K realistic for a machine learning engineer in New York?

That is the top of a posted range for one role at Ramp, not a typical offer. Actual pay depends on level, equity, and negotiation. Verify current ranges with the employer and with New York's pay transparency disclosures.

Why are so few roles entry-level?

Because the listings in this slice are for experienced hires. If you are early career, widen your search to adjacent analyst and operations titles and consider contract work to build the two years most of these roles ask for.

How long should I spend per application?

Twenty to thirty minutes for a targeted application, longer if there is a take-home. If you are spending two hours per application across dozens of roles, your targeting is off and your results will show it.