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Create CVThe demand for data professionals in the US has exploded, but not all data jobs pay equally. If you're searching for highest paying data jobs in the US, data science salary USA, or how much do data analysts make in the US, you're likely trying to answer one core question:
Which data roles actually lead to the highest income—and how do you get there?
This guide breaks down real compensation data, recruiter insights, and strategic positioning so you understand what you can realistically earn, how salaries are determined, and how to maximize your total compensation in data careers.
To dominate rankings, we address all layers of intent:
Primary intent: Identify highest-paying data jobs
Secondary intent: Understand salary differences by role and experience
Hidden intent: Learn how to break into high-paying data careers and increase earnings
Below are the most lucrative roles in data science and analytics based on US market data.
Average Salary (Base):
Total Compensation:
Top 1% (Big Tech / AI companies):
Why it pays high:
Direct revenue impact through AI products
High technical barrier (ML + software engineering)
Talent scarcity
Machine Learning Engineer: $160K – $250K+
Data Scientist: $130K – $220K
Data Engineer: $140K – $230K
Analytics Manager: $180K – $300K+
Quant Analyst: $200K – $500K+
BI Engineer: $120K – $180K
Data Analyst: $80K – $130K
Average Salary (Base):
Total Compensation:
Top performers:
Specializations that increase salary:
NLP (Natural Language Processing)
Computer Vision
AI/Deep Learning
Average Salary (Base):
Total Compensation:
Why demand is rising:
Companies need scalable data infrastructure
Critical for AI and analytics systems
Average Salary (Base):
Total Compensation:
Includes:
Team management
Strategic decision-making
Business impact ownership
Average Salary (Base):
Total Compensation:
Industries:
Hedge funds
Investment banks
Trading firms
Highest paying segment in data careers.
Average Salary (Base):
Total Compensation:
Average Salary (Base):
Total Compensation:
Entry point for most data careers.
Data Analyst: $60K – $85K
Data Scientist: $90K – $120K
Data Engineer: $95K – $125K
Data Scientist: $120K – $150K
Data Engineer: $130K – $160K
ML Engineer: $140K – $180K
Data Scientist: $150K – $200K
ML Engineer: $180K – $250K
Data Engineer: $160K – $220K
Director / Head of Data: $200K – $350K+
VP Data / AI: $300K – $600K+
In the US, base salary is only part of earnings.
Fixed annual income
Typically 60–80% of total compensation
Performance bonuses: 10–30%
Signing bonuses: $10K–$100K
Retention bonuses
Huge component in tech companies
Can add $50K–$300K+ annually
Healthcare
401(k) matching
Paid time off
Machine learning systems
Distributed systems (Spark, Hadoop)
Python + production engineering
AI/Deep Learning
Basic SQL reporting
Excel-based analysis
Non-technical analytics
Finance (Hedge funds, trading): $200K–$500K+
Big Tech (FAANG): $180K–$400K+
SaaS / AI startups: $150K–$300K+
Government: $70K–$120K
Non-profits: $60K–$100K
San Francisco: +20–40% premium
New York: +15–30%
Seattle: +10–25%
Increasingly normalized
Often slightly lower base, but similar total compensation
Internal leveling systems
Budget constraints
Market benchmarks
Candidate competition
Recruiters don’t ask:
They ask:
Strong portfolio vs theoretical knowledge
Production experience vs academic projects
Business impact vs technical execution
Weak Example:
“I built a model predicting house prices.”
Good Example:
“My model improved pricing accuracy by 18%, increasing revenue by $2M.”
Highest salaries are in:
ML Engineering
Data Engineering
Companies pay for:
Revenue generation
Cost reduction
Biggest salary jumps: 20–50%
Internal raises: 5–10%
Focus on:
Equity
Signing bonus
Title level
Staying too long in low-paying roles
Not negotiating offers
Focusing only on base salary
Avoiding high-paying industries
AI roles will dominate highest salaries
Data analysts without technical skills will plateau
Hybrid roles (data + engineering + business) will command premium pay
The highest paying data jobs in the US are not random—they are predictable.
They reward:
Technical depth
Business impact
Scarcity of skills
If you position yourself correctly, a data career can realistically scale from:
$70K entry-level
To $150K–$250K mid-career
To $300K–$500K+ at the top
The difference is not intelligence.
It’s strategy, positioning, and execution.
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