Data Scientist Jobs in New York: The 2026 Hiring Landscape

Data scientist jobs in New York are full-time roles building models, analytics pipelines, and decision systems for finance, big tech, consumer tech, and consulting employers across Manhattan, Brooklyn, and remote-NYC. Median total comp sits around $183,600 per Levels.fyi (May 2026), with entry-level at $102K to $170K and senior at $180K to $312K (Source: Levels.fyi). Demand is growing 34% nationally through 2034 per the BLS (Source: BLS Occupational Outlook).

The NYC data scientist market at a glance

The numbers are useful. The numbers also hide the most important fact about this market: "data scientist" in New York is not one job. It is four.

Who is actually hiring data scientists in NYC right now

The boards return one undifferentiated list. The hiring market behind that list splits cleanly into four archetypes, each operating on a different comp band, each filtering for a different stack signal, and each with a different entry path.

Wall Street and quant. JPMorgan, Goldman Sachs, Morgan Stanley, Two Sigma, Citadel, Bloomberg, BlackRock. This is where the largest concentration of NYC data scientist headcount lives. JPMorgan CEO Jamie Dimon told Bloomberg on May 21, 2026 that the bank will hire more AI specialists and fewer traditional bankers, with the focus on engineers and data scientists with an AI focus (Source: Bloomberg). The Wall Street tier pays in base-plus-bonus. JPMorganChase posts Senior Associate Data Scientist roles at $114K to $170K base (Source: Indeed), with annual bonuses on top that the postings don't show. Two Sigma's Summer 2026 Data Scientist internship pays $3,800 to $4,200 per week depending on degree (Source: Two Sigma). The intern floor at a quant shop is higher than the senior full-time floor at most non-tech employers.

Big tech NYC offices. Google, Amazon, Meta, TikTok, Apple. This tier sets the total-comp ceiling. Levels.fyi reports a median total comp of $298,500 for Google Data Scientists in the NYC area, with Amazon at $286,850 and a top-of-band reaching $723K+ (Source: Levels.fyi). TikTok posts NYC Senior Data Scientist roles at $136.8K to $292.6K base (Source: Indeed), with RSU stacks that push the offer well past base. The filter signal here is research depth and shipped models in production.

Consumer tech and fintech. Uber, Capital One, SoFi, Squarespace, Datadog, Ramp, Etsy, Peloton. This is the broadest tier and the one with the most listings turnover. Built In NYC shows Director-level data science at Capital One at $269K to $335K and SoFi senior staff at $173K to $297K (Source: Built In NYC). The entry floor on Built In ($72K to $116K) mostly reflects junior analytics roles being tagged as "data science" by aggregators; the real entry floor for someone with Python+SQL+ML and any shipped projects is closer to $130K in fintech and $150K+ in consumer tech.

Consulting and enterprise. Deloitte, McKinsey, BCG Gamma, Accenture, EY. Lower comp ceiling, broader portfolio of problems, much faster cycling between projects. The Levels.fyi median for McKinsey Data Scientists in the NYC area is $130,000 (Source: Levels.fyi), roughly half of Google NYC at the same role title. Consulting reads vendor certs and breadth; finance reads probability theory; big tech reads model evals and infra; consumer tech reads ship velocity. The boards collapse all four signals into one bullet list.

What NYC data scientists actually earn in 2026

The single most important number on this page is the spread, not the average.

The BLS national median for data scientists is $112,590 (May 2024) (Source: BLS Occupational Outlook). The Levels.fyi NYC average is $183,600 (Source: Levels.fyi). The Google NYC median is $298,500 and the Amazon NYC ceiling reaches $723K+ (Source: Levels.fyi). That is a 6.4x factor from BLS national median to Amazon top-of-band, and every aggregator headline number sits somewhere in the middle of that spread.

The implication for negotiating is direct. Quoting an aggregator base-salary average from ZipRecruiter or Glassdoor, or the BLS national median of $112,590, in a Wall Street or big-tech conversation forfeits six figures. The right anchor depends on which of the four archetypes is hiring. Levels.fyi's company-specific NYC pages are the cleanest source because they separate base, bonus, and equity. Indeed and Glassdoor numbers conflate base salary with total comp and conflate consulting bands with big-tech bands.

The senior band is the most stable signal. Levels.fyi puts NYC senior data scientist comp at $180K to $312.6K (Source: Levels.fyi). Anyone with three to five years of shipped ML work in NYC should treat $200K as a floor for total comp, not a stretch number. The entry band ($102K to $170K) is wider because it spans the consulting tier on the low end and the big-tech new-grad band on the high end.

The skill stack employers actually want

Skip the "you need 47 buzzwords" listicle. An analysis of 500 data science job posts in 2026 found Machine Learning required in 69% of postings, Python in 57%, R in 33%, and SQL in 30% (Source: Medium / Analyst Uttam). Python plus SQL plus ML carries the vast majority of postings. R still appears in finance and pharma where statistical inference is central. Cloud, data engineering, and GenAI tooling layer on top of the core stack, not in place of it.

A bachelor's in mathematics, statistics, computer science, or a related field is the BLS-confirmed baseline (Source: BLS Occupational Outlook). A master's or PhD is preferred at quant shops, research-heavy big-tech roles, and pharma. Outside those tiers, an MS is a tiebreaker, not a prerequisite. The fintech tier and the consumer tech tier hire bachelor's-plus-portfolio data scientists every week.

Why the job board listing counts don't match reality

Indeed says 1,005 (Source: Indeed). LinkedIn says 5,000+ in the city and 13,000+ in the metro (Source: LinkedIn). Glassdoor says 896. Dice says 246. SimplyHired says 608.

A 50x gap between LinkedIn metro and Dice for the same keyword in the same city in the same month is not a market-size signal. It is aggregator noise. The number of NYC data scientist openings with real hiring intent in a given week is closer to the Dice and Glassdoor band than the LinkedIn metro number. The rest is reposts, expired listings, sourcing-funnel ghost postings, and aggregator duplication across affiliate networks.

Three filters cut the listing flood to roles worth applying to. First, a job posted over 45 days ago is dead on arrival, whether filled, paused, or never real. Second, a posting with no named hiring manager and no engineering or data blog from the company is high-ghost-rate territory. Third, a posting that lists 12+ required tools and demands every one of them at expert level is almost always a recruiter-padded JD with no internal champion. Skip those three categories and the 1,005 Indeed number drops to a few hundred real opportunities. Skip ghost-jobs entirely with a separate filter set as covered in our ghost-jobs detection guide.

The application pile is the worst way in

When a single NYC data scientist requisition sits on LinkedIn and pulls hundreds of applications inside two weeks, the marginal application gets read for six seconds by a recruiter or routed through an ATS keyword filter before any human looks at it. From the matches Standout has run with hiring companies across US tech, the modal NYC data scientist requisition draws several hundred cold applications in the first two weeks, most of them auto-apply spam from outside the US, with a recruiter triage budget of roughly twenty to thirty resumes that get human eyes.

For a data scientist with a Python+SQL+ML stack and any real ML projects in production, getting matched into a direct intro to the hiring company beats getting buried in that pile. Application volume is not an advantage in this market. Signal is.

How Standout works for data scientists in NYC

Standout is an AI talent agent for tech professionals in the US, headquartered in San Francisco, founded by Alexis Aftalion (ex-Zealy) and Witold de La Chapelle (ex-Dropbox, Samsara, Chime) (Source: standout.work). The product matches a candidate with a hiring company. If the candidate says yes, Standout introduces them directly to the founder. The candidate stays anonymous until they accept an intro.

Three concrete things about how this works for a NYC data scientist:

• All US tech companies, seed through Series D. Standout works with any US tech employer (finance-adjacent, big tech, consumer tech, fintech, AI labs, infrastructure startups). Not YC-exclusive. The match flow operates the same way across all four NYC data scientist archetypes.
• All tech roles, not engineering-only. Data scientists are a meaningful slice of the candidates Standout represents, but the same mechanism runs across product, design, data, ML/AI, DevOps, marketing, sales, ops, customer success, and business development.
• Free for candidates, placement-fee on the company side. Candidates pay nothing. The company pays a placement fee only if a hire happens.

First matches arrive within a few hours of profile completion (Source: standout.work). Compare that to the four-month median tech job search timeline most NYC candidates report.

What a data scientist's first 30 days on Standout looks like

The flow is short. Build the anonymous profile (skills, level, target comp, NYC + remote-US preference). The matching engine ingests the profile and starts pushing matches inside hours. Each match is a hiring company that fits the candidate's stack, level, and comp band. The candidate accepts or declines per match. No cold application, no resume pile, no recruiter ghosting. On accepted matches, Standout introduces the candidate directly to the founder or hiring manager. The candidate's identity stays anonymous until they accept the intro.

The candidates Standout represents at the data scientist level tend to be three to seven years in, shipping ML or analytics that touches revenue or operations directly, with a clear preference signal on which archetype they want next. The matches that close fastest are the ones where the candidate has already decided whether they want Wall Street tier, big tech tier, or fintech tier. The matching engine cuts harder when the candidate's preference is sharp.

For ML-heavy candidates, the ML engineer NYC overview covers the adjacent specialty. For broader engineering search, see software engineer jobs in New York. The mechanics covered in how Standout's matching engine works apply across all roles.

FAQ

What's the average data scientist salary in New York City in 2026?

Levels.fyi puts the NYC area average at $183,600 total comp, with a typical range of $136,000 to $250,000 (Source: Levels.fyi). The senior band runs $180,000 to $312,600. Big-tech medians sit higher (Google NYC $298,500, Amazon NYC $286,850); consulting medians sit lower (McKinsey NYC $130,000).

Which companies hire the most data scientists in NYC?

Wall Street and quant (JPMorgan, Goldman Sachs, Two Sigma, Citadel, Bloomberg), big tech (Google, Amazon, Meta, TikTok, Apple), consumer tech and fintech (Uber, Capital One, SoFi, Squarespace, Datadog, Ramp), and consulting (Deloitte, McKinsey, BCG Gamma) carry most of the volume (Source: Built In NYC). Each tier pays differently and filters for different signals.

Do I need a master's or PhD to get a data scientist job in NYC?

A bachelor's in math, statistics, computer science, or a related quantitative field is the BLS baseline (Source: BLS Occupational Outlook). An MS or PhD is preferred at quant shops and research-heavy big-tech roles but is not required at fintech, consumer tech, or consulting. A portfolio of shipped ML work matters more than the degree at most non-quant employers.

Is the New York data scientist market actually growing in 2026?

Yes. The BLS projects 34% growth for data scientist employment between 2024 and 2034, with about 23,400 openings nationally per year (Source: BLS Occupational Outlook). NYC is overweight on that growth because of the AI hiring shift at large banks. JPMorgan said on May 21, 2026 it will hire more AI specialists and fewer traditional bankers (Source: Bloomberg).

What's the fastest way to get a data scientist job in NYC without cold applying?

Get matched, not added to a pile. The boards return thousands of listings (Indeed 1,005, LinkedIn metro 13,000+, Glassdoor 896) but most carry no real hiring intent and the rest pull hundreds of applications inside two weeks. Standout matches candidates with hiring companies and introduces them directly to the founder, with first matches arriving within hours of profile completion (Source: standout.work). Free for candidates.

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Skip the application pile. Standout matches data scientists with hiring NYC companies and introduces you directly to the founder. Free for candidates. First matches within hours.