Exploring data and AI jobs in the United States

Use this page to compare Data & AI openings in United States. Check the actual work location, responsibilities, experience requirements and employment arrangement before applying. A country-level indicator is context; it cannot confirm that a particular employer or city is hiring.

Choose the work you want to own

An analyst role may focus on metrics and reporting; an engineering role may focus on pipelines and reliable data access. Data science roles may involve experiments or predictive modeling, while AI application roles may involve model integration and evaluation. Titles overlap. Compare the deliverables and review process in each advertisement.

Compare locations and work arrangements

Separate the advertised city from the states in which remote employment is allowed. Check office attendance, time-zone expectations and relocation requirements with the employer. A national trend cannot establish demand in Boston, New York or another individual market.

Evaluate pay using the right population

Start with the advertised range in the stated currency and separate base salary, bonus, equity and benefits. If using a published wage series, check its occupation, geography and measurement year. An occupational median does not identify an entry-level or senior salary.

Prepare evidence for the opening

Choose a project that matches a required deliverable and explain how you checked it. Use public or synthetic data for a shareable portfolio. Ask which AI tools are permitted in the assessment; be able to discuss the work independently.

Check credentials before enrolling

Use the provider’s current catalog and the role’s eligibility requirements. A historical credential can be accurately listed on a CV, but a retired exam should not be recommended as a current enrollment option.

Sources and next steps

Role and credential sources checked on October 2, 2026.

Microsoft Learn: data analyst role

Google Cloud: data engineer role

Microsoft credential retirement notices

Salary sources and limitations