Business Intelligence Analyst (15-2051.01)
Career Family
Computer & Mathematical → Data Analytics & BI
Fit Summary
Investigative (I) with Conventional (C) and Enterprising (E); MBTI often INTJ/ISTJ/ENTP—quant, curious, stakeholder-facing.
Career Overview
Model and analyze business data; build dashboards and reports; discover trends and opportunities; partner with teams to define metrics and support decisions.
Credential Pathways
Typical Education: Bachelor’s in analytics/CS/statistics/business; certifications (BI tools/SQL) valued; Job Zone 4–5.
Pathways: Analyst → senior → analytics engineer/BI lead → data product manager.
Regulatory Moat: Data governance, privacy, and access controls; documentation standards.
Alternative Pathways: Operations/finance → self-taught SQL + BI projects; bootcamps and portfolios.
Environment & Lifestyle
- Work Environment: Office/remote; sprints with product/ops/finance; ad hoc asks around launches/close.
- Sensory/Social Load: High—requirements gathering and stakeholder comms.
- Physicality/Fieldwork: Low—desk-based.
- Geographic Anchoring: Across industries; strong in tech/finance/ops hubs; many remote roles.
- Remote Amenability: Very high—data work and collaboration online.
Future-Proofing Snapshot
- AI Augmentation Potential: Very high — automated insight surfacing, NL-to-SQL, forecasting.
- AI Displacement Risk: Low-Medium — basic reporting automates; consultative analysis persists.
- AI New Task Creation: High — semantic layer stewardship, decision intelligence.
- AI Skill Shift Intensity: High
- Automation Risk Score: Low-Medium
- Human-Core Score: High — problem framing, communication, domain context.
- Overall Vulnerability/Resilience: Resilient for analysts who pair SQL with storytelling and product sense.
- Emerging Trends: Metrics layers, reverse ETL, self-serve analytics, causal methods.
Risks / Watchpoints
- Dashboard sprawl
- Data quality debt
- Misinterpretation of metrics
Notes on Fit
Great for pattern-spotters who translate data into clear decisions.
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