Data Scientist Salary New York 2026: Finance, Tech, and Beyond

New York City sits at the intersection of two of the world's most data-hungry industries: global finance and large-scale consumer technology. For data scientists, this creates a genuinely unique market — one where a Goldman Sachs quantitative analyst and a Google staff data scientist may work three blocks apart but operate under completely different compensation philosophies.

In 2026, understanding that dual market is the difference between accepting a good offer and negotiating the right one.

For a broader view across experience levels and cities, see the Data Scientist Salary Guide 2026.

---

NYC Data Scientist Salary by Level (2026)

Total comp figures include annual cash bonus (typical in finance) or RSU vesting (typical in tech). Finance bonuses are often 20–50% of base for senior roles; FAANG RSU grants typically vest over four years and compound with refresh cycles.

---

Finance vs Tech: Two Very Different Compensation Philosophies

Finance and Fintech (Goldman Sachs, JPMorgan, Bloomberg, Two Sigma, Citadel, Renaissance Technologies)

New York's finance sector is the world's largest concentration of quantitative talent. Goldman Sachs, JPMorgan, and Bloomberg employ thousands of data scientists across risk modeling, trading analytics, fraud detection, and customer behavior. Hedge funds like Two Sigma, Citadel, and Renaissance Technologies sit at the extreme end — compensation for senior quantitative researchers regularly exceeds $500K–$1M+ in total comp, blending base salary with performance-linked bonuses tied directly to fund returns.

The defining characteristic of finance data science compensation is cash-heavy structure. A senior data scientist at a major bank might earn $170,000 base with a $50,000–$80,000 annual cash bonus — $220,000–$250,000 in cash that lands in your account each year, with minimal equity exposure. This predictable cash flow is exceptionally attractive compared to RSU-heavy tech comp where realized value depends on stock performance. Bloomberg's data and analytics division, for example, is known for reliable cash-heavy packages that attract engineers who want financial certainty over tech equity upside.

Quant funds operate differently still. Two Sigma, Citadel, and Renaissance are more selective than FAANG — they hire fewer people but pay dramatically more. A mid-level researcher at a top-tier hedge fund typically out-earns a FAANG L6 equivalent by 40–70%, with the trade-off of longer hours, high performance pressure, and compensation that varies with fund performance.

Tech (Google, Meta, Amazon)

Google, Meta, and Amazon all maintain large New York engineering and data science presences. Google's NYC office focuses heavily on ads, search quality, and Maps data infrastructure. Meta's NYC teams cover ads measurement, Reels optimization, and commerce analytics. Amazon's NYC data science teams support retail, advertising, and AWS enterprise sales analytics.

FAANG data science comp in NYC follows the standard equity-heavy structure. A senior data scientist at Google (L5) might earn $165,000–$185,000 base, $35,000–$45,000 bonus, and $200,000–$280,000 in RSUs vesting over four years — approximately $250,000–$340,000 annually in steady-state total comp. The equity upside is real, but stock price volatility means year-to-year realized compensation varies significantly.

The key dynamic in NYC: finance firms and tech companies often compete for the same mid-career data scientists. A Goldman analytics engineer getting recruited by Google can legitimately leverage that competition in both directions. NYC's dense job market makes this cross-sector negotiation more achievable than in any other city.

---

NYC vs Other Major Data Science Markets (2026)

Seattle's zero state income tax advantage is meaningful. A data scientist earning $170,000 in Seattle takes home approximately $12,000–$16,000 more per year after taxes than an equivalent earner in NYC. San Francisco offers the highest nominal salaries but California's 9.3% state tax and the city's extraordinary cost of living often make NYC a better net-value proposition, especially for finance-oriented data scientists.

For more on the Berlin market, see Data Scientist Salary Berlin 2026.

---

Stack Premiums in NYC

Not all data science skills are valued equally in New York's dual-sector market.

Universal high-value skills:

Python (core) — standard across all sectors, no premium but essential

SQL — deep query optimization and data modeling skills command 10–15% above average

PyTorch / TensorFlow — deep learning frameworks add 15–25% premium at tech companies

Finance-specific premiums:

Time-series modeling (ARIMA, Prophet, LSTM for financial data) — significant premium at banks and quant funds

R — still widely used in quantitative research; bilingual Python/R candidates valued

Apache Spark — large-scale financial data processing; required at many bank analytics teams

Quantitative finance domain knowledge — risk modeling, options pricing, market microstructure; premium of 25–40% at specialized firms

Tech-specific premiums:

ML platform tools (MLflow, Kubeflow, Metaflow) — 10–20% premium at FAANG and scale-ups

Distributed computing (Spark, Flink, Dask) — valuable for large-scale experimentation and feature engineering

A/B testing and causal inference — experimental design expertise is highly valued at product analytics roles

---

The NYC Tax Reality

New York City data scientists face the highest combined income tax burden of any major US tech hub. New York state applies a 6.85% marginal rate on income above $215,400, and NYC city adds a further 3.876% on top. Combined with federal taxes (24–32% marginal on this income range), effective total tax rates for senior data scientists reach 38–42% of gross compensation.

Practical example: A senior data scientist earning $175,000 base plus a $50,000 bonus ($225,000 total) pays approximately $85,000–$95,000 in total taxes, leaving $130,000–$140,000 net annually. After a $3,500/month Manhattan apartment ($42,000/year), transportation ($2,400/year), and living expenses, disposable income is comfortable but modest relative to the nominal salary.

Engineers seeking to maximize take-home frequently consider Brooklyn or Long Island City (Queens) for housing — 20–30% cheaper than Manhattan while maintaining subway access to Midtown and the Financial District.

---

NYC Salary Transparency Law

New York City's salary transparency law requires employers with four or more employees to post salary ranges on all job listings. In practice, this gives data scientists real leverage: you can see the employer's ceiling before investing time in the process.

When you see a posting for "Senior Data Scientist: $150,000–$220,000," the posted ceiling is real. Strong candidates with quantitative finance backgrounds or ML specializations should aim at or above the midpoint of the range, anchoring based on your specific stack premium and the cross-sector competition visible from comparable postings.

For deeper context on the NYC tech market overall, see Tech Salaries New York 2026 and ML Engineer Salary New York 2026.

---

Related Salary Guides

Data Scientist Salary Guide 2026 — global data scientist salaries across 7 cities

Data Scientist Salary Berlin 2026 — Berlin's startup-heavy market vs NYC finance

ML Engineer Salary Guide 2026 — machine learning engineer salaries globally

Tech Salaries New York 2026 — complete NYC tech salary breakdown by role

New York in 2026 is the only city in the world where a data scientist can credibly compare offers from a top-tier hedge fund and a FAANG office within the same job search. That competition drives salaries higher and gives well-prepared candidates genuine negotiating leverage — but only if you understand the different compensation logic each sector uses.

Benchmark your NYC data science salary against live market data: data scientist salary data →