Data & Analytics
Turning raw data into decisions and ensuring data quality for AI systems. Covers data analysis, data science (business analytics context), data engineering (analytics platform context), analytics engineering, BI, data governance, data platform engineering, applied ML for business use cases, and ML data annotation operations management.
Roles
The canonical roles within Data & Analytics.
Data Scientist
Applies statistical modeling, machine learning, and experimentation to extract insights from data.
Data & Business Analyst
Analyzes data to generate actionable business insights, builds dashboards and reports.
Marketing & GTM Analytics
Data professionals specializing in marketing and go-to-market measurement, attribution modeling, and revenue intelligence. Focuses on building analytical frameworks, experimentation, and data-driven insights to optimize GTM strategy. The emphasis is on analytics methodology and data infrastructure for marketing.
Data Engineer
Builds and maintains data pipelines, warehouses, and infrastructure that enable analytics and ML.
Analytics Engineer
Bridges data engineering and analytics by building data models, metrics layers, and self-serve analytics tools.
ML Data & Annotation Operations
Manages data labeling, annotation, and curation operations for machine learning.
Data & Analytics Leader
Provides leadership for data science, analytics, or data engineering teams.
Recent Jobs
The latest Data & Analytics openings across the AI industry.