AI Analyst job description.
An AI Analyst evaluates, implements, and monitors artificial intelligence and machine learning tools to solve business problems and improve decision-making. They translate business requirements into AI use cases, assess model performance, and work with technical teams to deploy solutions responsibly.
The AI Analyst job description · $29
The full editable .docx — role summary, 8 worked responsibilities, qualifications, and skills, formatted for your letterhead. Delivered to your inbox within 24 hours — usually instantly.
Role: AI Analyst Reports to: Data Science Manager or Director of Analytics
An AI Analyst evaluates, implements, and monitors artificial intelligence and machine learning tools to solve business problems and improve decision-making. They translate business requirements into AI use cases, assess model performance, and work with technical teams to deploy solutions responsibly.
- Identify business processes that could benefit from AI or automation
- Evaluate and recommend AI tools, models, or vendors for specific use cases
- Analyze data quality and readiness to support AI model development
What's inside the document.
One-paragraph plain-English explanation of the role's outcome and scope.
8 responsibilities phrased the way the work is actually done.
4 qualifications a candidate must have to perform on day 30.
2 qualifications that would make a candidate excellent in year two.
6 skill chips you can copy directly into your ATS.
Data Science Manager or Director of Analytics
A complete document set.
- Word document (.docx) — fully editable
- PDF — signature-ready
- Google Docs — one-click copy to your Drive
- 12 months of updates to this document
- Commercial-use licence for internal and client work
The work, not the title.
- Identify business processes that could benefit from AI or automation
- Evaluate and recommend AI tools, models, or vendors for specific use cases
- Analyze data quality and readiness to support AI model development
- Monitor deployed AI models for accuracy, bias, and performance drift
- Collaborate with data science and engineering teams on implementation
- Document AI use cases, assumptions, and limitations for stakeholders
- Translate technical AI capabilities into plain-language business impact
- Stay current on AI governance, ethics, and regulatory considerations
Required — and what would make a candidate excellent.
- Bachelor's degree in data science, computer science, or related field
- 2+ years of experience working with data analysis or AI/ML tools
- Proficiency with SQL and a scripting language such as Python
- Ability to translate technical findings for non-technical audiences
- Experience with large language models or generative AI platforms
- Familiarity with AI governance or responsible AI frameworks
Eight steps from download to publish.
- 01Open the AI Analyst job description in Word or your one-click Google Docs copy.
- 02Replace placeholders for company name, reporting line, and location with your specifics.
- 03Tighten the summary to one paragraph that names the team's outcome, not just the role.
- 04Edit the responsibilities to match the actual scope of the seat — aim for 6 to 8 items, not 12.
- 05Separate required qualifications from preferred. Required is what a candidate must have to do the work on day 30; preferred is what would make them excellent in year two.
- 06Add salary range guidance using BLS, Payscale, or your own band data — do not copy generic figures.
- 07Have the hiring manager and one peer read it. Cut anything that wouldn't survive a candidate question.
- 08Publish to your ATS, intranet, and external careers page.
The right document at the right moment.
Use this AI Analyst job description any time you are opening or reopening a seat at this level. The mid band sets the calibration — copy the document, tighten it to your specific scope, and circulate to the hiring panel before the first interview.
The reporting line (Data Science Manager or Director of Analytics) and skills list are starting points. Override either if your org structure or stack differs from the norm — the template is a draft, not a contract.
Honest answers before you download.
- How is an AI Analyst different from an AI Engineer?
- The analyst focuses on evaluating use cases, data readiness, and model performance from a business perspective, while the engineer builds and maintains the underlying models and systems.
- Does this role require advanced coding skills?
- Working knowledge of SQL and Python is typically enough; deep model-building expertise is usually handled by data scientists or AI engineers.
Other documents in this neighbourhood.
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Business Intelligence Analyst
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AI Engineer
An AI engineer designs, builds, and deploys machine learning models and AI-powered systems that solve business problems.
This AI Analyst job description is a professionally drafted starting point for your hiring process and is not legal advice. Hiring practice varies by jurisdiction (e.g. pay-transparency laws differ across US states and AU jurisdictions). Adapt this document for your specific location and have employment counsel review any clauses you add before publishing. Salary varies by region, employer type, and experience. Reference BLS or current industry surveys for ranges. Full disclaimer.