Job Description
Join the architects of tomorrow at Horizon Dynamics Inc. We're seeking visionary pioneers to shape humanity's trajectory toward 2026 and beyond. As a premier innovation consultancy, we decode emerging technologies, societal shifts, and market disruptions to guide Fortune 500 leaders into the future. This is your chance to influence how the world adapts to AI singularity, quantum computing, and climate resilience paradigms.
Our San Francisco hub operates at the intersection of biotech, AI ethics, and sustainable infrastructure. You'll collaborate with Nobel laureates, Silicon Valley disruptors, and UN policymakers to develop actionable 5-year strategic roadmaps. This isn't just forecasting—it's active creation of preferred futures.
Responsibilities
- Develop predictive models for 2026 market landscapes across tech, energy, and healthcare sectors
- Lead scenario-planning workshops with C-suite executives on existential risks and opportunities
- Produce white papers on disruptive technologies' societal impacts (quantum AI, neuro-interfaces, climate geo-engineering)
- Advocate for ethical frameworks in emerging tech adoption at global forums
- Build proprietary foresight tools using NLP and predictive analytics
- Partner with MIT Media Lab and Singularity University on horizon-scanning initiatives
- Design resilience strategies for systemic collapse scenarios (supply chains, financial systems, democratic institutions)
Qualifications
- Master's degree in Futures Studies, Systems Theory, or equivalent experience
- 5+ years in strategic foresight, innovation consulting, or policy analysis
- Published work on technological singularity or climate adaptation (peer-reviewed journals preferred)
- Proficiency in foresight methodologies: Delphi, Horizon Scanning, Cross-Impact Matrices
- Expertise in AI ethics frameworks (EU AI Act, NIST RMF) and quantum computing applications
- Experience with scenario planning tools (e.g., Causal Layered Analysis, STEEP-V)
- Fluency in at least one predictive analytics platform (Python/R required)
- Portfolio demonstrating successful 5+ year predictive accuracy (minimum 80%)