Data Scientist vs Enterprise Architect: Which Pays More?
Side-by-side salary comparison by city, experience level, and career growth outlook. Data reflects current market rates.
Data Scientist
Analyse large datasets and build predictive models to drive decisions.
Enterprise Architect
Align IT architecture with business strategy at the enterprise level.
Data Scientist earns more on average — the national median is $3,650/year (3%) higher than a Enterprise Architect. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
Data Scientist vs Enterprise Architect — Salary by City
National median figures in USD across top cities.
| City | Data Scientist | Enterprise Architect | Difference |
|---|---|---|---|
| San Francisco, CA | $176,777 | $174,584 | Data +$2,193 |
| New York, NY | $135,980 | $138,849 | Data $2,869 |
| Seattle, WA | $173,186 | $170,016 | Data +$3,170 |
| Austin, TX | $130,733 | $128,905 | Data +$1,828 |
| Chicago, IL | $132,415 | $126,306 | Data +$6,109 |
| Boston, MA | $156,115 | $150,648 | Data +$5,467 |
| London, UK | £78,216 | £92,059 | Data $13,843 |
| Toronto, Canada | CA$134,265 | CA$158,112 | Data $23,847 |
Frequently Asked Questions
Does a Data Scientist or Enterprise Architect earn more?+
A Data Scientist earns more on average. The national median salary for a Data Scientist is $120,230/year, compared to $116,580/year for a Enterprise Architect — a difference of $3,650 (3%).
Which has better career growth — Data Scientist or Enterprise Architect?+
Data Scientist roles are growing at 36% YoY while Enterprise Architect demand is growing at 18% YoY. Data Scientist has stronger near-term demand growth.
Can you switch from Data Scientist to Enterprise Architect?+
Yes. Many professionals transition between these roles, especially since both are in the same category. Shared skills include: analytical thinking, communication, and industry knowledge.
Which is harder to automate — Data Scientist or Enterprise Architect?+
Enterprise Architect has a lower AI automation risk (25% vs 40%). Based on Oxford Martin School and McKinsey 2023 analysis.