Data & AnalyticsJobs - SQL, Python, BI, AI
Data analyst, analytics engineer, and data science jobs hiring now. Find SQL, Python, dbt, BI, product analytics, and AI data roles at top tech companies. $120k-$220k, updated daily.
Data Scientist (AI/ML) | Contract | Financial Services
Senior Country Approval Specialist / Principal Ctry Approval Specialist
Data and analytics jobs cover data analyst, analytics engineer, business intelligence, data science, and product analytics roles. The strongest searches in this category usually include SQL jobs, Python data jobs, remote data analyst jobs, dbt analytics engineering, and AI data science roles.
Modern data teams work across product metrics, experimentation, customer analytics, revenue reporting, and machine learning datasets. Common tooling includes SQL, Python, dbt, Snowflake, BigQuery, Looker, Tableau, Amplitude, and notebooks for deeper analysis.
AI companies also hire data specialists for evaluation datasets, model quality analysis, annotation operations, fraud detection, and go-to-market analytics. Candidates who can combine statistical reasoning with clean stakeholder communication tend to stand out in these searches.
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Frequently Asked Questions
What skills do data analyst jobs require?
Most data analyst jobs require strong SQL, spreadsheet fluency, dashboarding, and clear written communication. Python, statistics, experimentation, dbt, and product analytics tools such as Amplitude or Mixpanel make candidates more competitive for tech and AI company roles.
What is the difference between data analyst and analytics engineer?
Data analysts focus on answering business and product questions through reporting, metrics, and analysis. Analytics engineers focus more on building trusted data models, pipelines, dbt projects, and semantic layers that analysts and product teams rely on.
Are there remote data jobs?
Yes. Remote data analyst, analytics engineer, and data science jobs are common at startups and distributed tech companies. Remote roles usually expect strong async communication, reproducible analysis, and comfort working with cloud data warehouses.