Entry Level Data Analyst Ai information
See Remote, OR salary details
$13.21 - $17.62
10% of jobs
$20.87 is the 25th percentile. Wages below this are outliers.
$17.62 - $22.03
20% of jobs
$22.03 - $26.44
18% of jobs
The median wage is $27.03 / hr.
$26.44 - $30.85
16% of jobs
$34.08 is the 75th percentile. Wages above this are outliers.
$30.85 - $35.26
16% of jobs
$35.26 - $39.67
6% of jobs
$39.67 - $44.08
3% of jobs
$44.08 - $48.49
4% of jobs
$48.49 - $52.90
3% of jobs
$52.90 - $57.31
2% of jobs
$57.31 - $61.72
2% of jobs
How much do entry level data analyst ai jobs pay per hour?
As of Aug 17, 2026, the average hourly pay for entry level data analyst ai in Remote, OR is $32.89, according to ZipRecruiter salary data. Most workers in this role earn between $21.15 and $36.73 per hour, depending on experience, location, and employer.
Entry level data analyst AI jobs involve collecting, cleaning, and interpreting data to help organizations make informed decisions, with a focus on supporting artificial intelligence projects. These roles may include preparing datasets for machine learning models, analyzing trends, and creating reports or visualizations. While these positions require strong analytical and problem-solving skills, they are suitable for those beginning their career in data analysis and AI, often requiring knowledge of basic programming languages, statistics, and data tools.
To thrive as an Entry Level Data Analyst, you need a solid understanding of statistics, data cleaning, and foundational analytics concepts, often supported by a degree in a related field such as mathematics, statistics, or computer science. Familiarity with tools like Excel, SQL, and data visualization software (e.g., Tableau or Power BI), as well as basic knowledge of programming languages like Python or R, is typically expected. Attention to detail, problem-solving ability, and effective communication are crucial soft skills for clearly interpreting and presenting data insights. These skills and qualifications are vital for accurately analyzing data, supporting business decisions, and effectively collaborating with team members.
Entry-level Data Analysts in AI projects often face challenges such as understanding complex data structures, adapting to rapidly evolving tools, and interpreting results from advanced machine learning models. Collaborating closely with data scientists and engineers can help bridge knowledge gaps and foster learning. Staying proactive in seeking mentorship, participating in code reviews, and dedicating time to continuous learning are effective strategies to overcome these hurdles and quickly grow in the role.
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