Data Analytics, HR & Operations Skills¶
9 skills with 28 Python tools covering data engineering, business intelligence, ML ops, talent acquisition, people analytics, and operations management.
Data & Analytics¶
5 skills with 16 tools for data analysts, data scientists, analytics engineers, and ML ops engineers.
| Skill | Description | Tools |
|---|---|---|
| data-analyst | SQL querying, data visualization, statistical analysis, business reporting, data storytelling | 3 |
| data-scientist | Machine learning, statistical modeling, experimentation, predictive analytics | 3 |
| analytics-engineer | dbt development, star schemas, staging/mart models, semantic layer | 4 |
| business-intelligence | Dashboard design, KPI frameworks, reporting automation, executive insights | 3 |
| ml-ops-engineer | Model deployment, ML pipelines, monitoring, feature stores, infrastructure | 3 |
HR & Operations¶
4 skills with 12 tools for HR professionals, recruiters, and operations managers.
| Skill | Description | Tools |
|---|---|---|
| talent-acquisition | Recruiting strategy, candidate sourcing, interview design, employer branding, hiring analytics | 3 |
| people-analytics | Workforce analytics, turnover prediction, engagement surveys, HR metrics | 3 |
| hr-business-partner | Talent strategy, org development, employee relations, performance review cycles | 3 |
| operations-manager | Process optimization, operational efficiency, resource management, continuous improvement | 3 |