Data Analyst
$109,361
avg. annual salary
Ai/ml Engineer
pays more on average
Ai/ml Engineer
$109,979
avg. annual salary
As technology continues to evolve, the demand for professionals in data-driven roles has surged. Among these, Data Analysts and AI/ML Engineers are two pivotal positions that play a significant role in shaping business strategies. Understanding the salary differences, benefits, and career trajectories of these roles can help you make an informed career choice. In 2025, the salary landscape for Data Analysts tends to be steady while AI/ML Engineers see significant growth due to the increasing reliance on artificial intelligence in various industries. This article provides a thorough comparison to help you evaluate which path aligns better with your career aspirations and financial goals.
Salary by Experience Level
starting salary
starting salary
avg. difference (1%)
Salary Overview
In 2025, the average salary for Data Analysts is approximately $85,000, while AI/ML Engineers enjoy an average salary of about $120,000. The salary range for Data Analysts typically spans from $60,000 to $115,000, depending on experience, location, and industry.
On the other hand, AI/ML Engineers generally earn between $95,000 and $160,000. Factors like advanced skill sets and industry demand can influence these figures.
Benefits Comparison
Alongside salaries, benefits play a crucial role in total compensation. Data Analysts usually receive standard benefits including health insurance, retirement plans, and paid time off.
In contrast, AI/ML Engineers often enjoy additional perks such as stock options, more extensive training and development programs, and flexible work arrangements. These benefits can significantly enhance the overall job satisfaction and work-life balance for both roles.
Career Paths and Opportunities
Data Analysts often start as junior analysts and can progress to senior analyst or managerial roles. Their career path may lead to positions such as Data Scientist or Business Intelligence Analyst.
AI/ML Engineers, conversely, have opportunities to move into specialized areas like AI Research Scientist or Machine Learning Architect. The rapid growth of AI technology ensures that AI/ML Engineers have robust career advancement opportunities in innovative sectors.
Skills and Qualifications
Data Analysts typically require skills in data visualization, statistical analysis, and proficiency with tools like SQL and Excel. A bachelor’s degree in data science, statistics, or a related field is often sufficient.
In contrast, AI/ML Engineers need strong programming skills (often in Python or Java), knowledge of machine learning algorithms, and familiarity with big data technologies. A master’s degree or relevant certifications are frequently expected.
Detailed Salary and Role Comparison (2025)
### Base salary ranges
- •Data Analyst: typically $60,000–$110,000 in the U.S.; median around $80,000. Entry-level ~ $50K–$65K; senior/lead $100K–$140K.
- •AI/ML Engineer: typically $110,000–$220,000; median near $150,000. Entry-level ~ $100K–$130K; senior/engineering manager $180K–$260K.
### Typical responsibilities
- •Data Analysts focus on dashboards, SQL queries, A/B testing, and monthly reports.
- •AI/ML Engineers build and deploy models, manage data pipelines, and optimize inference (latency/cost).
### Real-world example
- •A retail analyst improves conversion by 6% using cohort analysis. An ML engineer reduces recommendation latency by 40% via model distillation.
Actionable takeaway: expect AI/ML roles to pay ~60–90% more on median but require deeper engineering skills and deployment experience.
Key Factors That Influence Salary
### Location and company size
- •Major tech hubs (SF, NYC, Seattle) pay 20–40% above national averages. Startups may offer equity instead of high base pay.
### Skillset and tools
- •SQL, Excel, Tableau = baseline for analysts. R or Python + ML libraries (PyTorch, TensorFlow) + MLOps skills raise AI/ML pay by 25–50%.
### Experience and role level
- •Moving from junior to mid-level often increases pay 30–50%. Lead or manager roles add another 30%+. Portfolio of shipped projects matters.
### Industry demand
- •Finance and healthcare frequently pay 10–30% more for domain expertise.
Actionable takeaway: target in-demand tools (model deployment or BI) and one high-paying industry to boost salary quickly.