Data Scientist
$117,111
avg. annual salary
Data Scientist
pays more on average
Site Reliability Engineer
$116,411
avg. annual salary
Understanding the salary dynamics between a Data Scientist and a Site Reliability Engineer (SRE) can significantly influence your career decision. These two roles, while both critical in tech ecosystems, serve very different functions. A Data Scientist typically focuses on analyzing and interpreting complex data to help businesses make informed decisions, while a Site Reliability Engineer ensures that the systems and services run smoothly and efficiently. This guide will delve into the salary ranges, benefits, job responsibilities, and career advancement opportunities for both roles, helping you determine which path may be more suited to your skills and aspirations.
Salary by Experience Level
starting salary
starting salary
avg. difference (1%)
Salary Overview
As of 2025, the average salary for a Data Scientist is approximately $110,000, with a range from $90,000 to $130,000 depending on experience and location. Conversely, Site Reliability Engineers earn an average salary of around $115,000, typically ranging from $95,000 to $140,000.
This difference often reflects the demand for SREs in managing operational stability and performance.
Benefits Comparison
Both roles offer competitive benefits, including health insurance, retirement plans, and flexible work arrangements. Data Scientists often enjoy additional perks like professional development opportunities, data-related conferences, and advanced training.
In contrast, Site Reliability Engineers may have more focus on work-life balance due to the nature of on-call duties, leading to additional compensatory time off and bonuses for incident response.
Career Paths
A Data Scientist can progress to higher-level roles such as Senior Data Scientist, Data Science Manager, or Chief Data Officer. The path typically emphasizes analytical skills and strategic decision-making.
On the other hand, a Site Reliability Engineer may advance to roles like Senior SRE, Engineering Manager, or Chief Technology Officer, with a focus on system reliability, infrastructure management, and engineering best practices.
Detailed Salary Comparison: Data Scientist vs Site Reliability Engineer
Overview
- •Entry level (0–2 years): Data Scientist base typically $70k–$95k; SRE base $90k–$120k.
- •Mid level (3–7 years): Data Scientist base $95k–$140k; SRE base $130k–$170k.
- •Senior (7+ years): Data Scientist base $140k–$180k+; SRE base $170k–$250k+.
Total compensation
- •Bonuses and equity commonly add 10%–40% to base pay. At big tech, SRE total comp can exceed base by 30%–50% because of RSUs and on-call premiums. Data Scientists in finance or ad tech often see 20%–35% uplift through bonuses and stock.
Real-world example: a senior SRE in SF might earn $200k base + $80k RSU = $280k total; a senior Data Scientist in SF might earn $165k base + $50k RSU = $215k total.
Actionable takeaway: Compare base, bonus, and equity separately; use role level and geography to set target ranges.
Key Factors That Affect Salary — What to Watch
Experience and scope
- •Years in role: each 3–5 year jump often increases base pay 15%–30%.
- •Impact: owning production systems (SRE) or shipping models that drive revenue (Data Scientist) increases leverage.
Technical skills
- •SRE: cloud platforms (AWS/GCP), Kubernetes, Linux, networking — premium of 5%–20%.
- •Data Scientist: production ML, SQL, feature engineering — premium of 5%–20%.
Company and location
- •Geography: Bay Area/NY salaries typically 20%–40% higher than national average.
- •Industry: finance and ad tech pay more; startups trade higher equity for lower base.
Work patterns and perks
- •On-call requirements for SREs can justify 5%–15% extra pay or stipends.
Negotiation tips
- •Benchmark offers with salary tools, ask 5%–15% above a strong offer, and quantify your impact with metrics (revenue saved, latency reduced, model lift%).
Actionable takeaway: Match your skill gaps to role premiums, then negotiate base + equity separately using concrete impact numbers.