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Consulting 🏢 Full Time ⭐️ Verified

2026 Futurist Strategist

Horizon Dynamics Inc.
Austin
Estimated Salary
USD 120.000 – USD 180.000
Live Update
21 Mei 2026
Deadline
21 Mei 2027

Job Description

Join Horizon Dynamics Inc. as a 2026 Futurist Strategist and help shape tomorrow's reality today. We're seeking visionary thinkers to decode emerging trends across biotechnology, quantum computing, and sustainable infrastructure. This role blends data analysis with creative foresight to develop actionable roadmaps for our clients navigating the 2026 landscape.

Why Join Us? Be at the forefront of innovation in Austin's thriving tech ecosystem. We offer competitive compensation, flexible work arrangements, and opportunities to present at global futurist conferences. Our team of Nobel laureates and industry pioneers will mentor you in cutting-edge methodologies.

Responsibilities

  • Analyze emerging 2026 market trends using AI-driven trend forecasting platforms
  • Develop scenario-planning frameworks for clients in renewable energy and space exploration sectors
  • Lead cross-functional workshops to translate foresight into strategic implementation plans
  • Author quarterly 'FutureScan' reports published in industry journals
  • Collaborate with quantum computing labs to model socio-technological impacts
  • Design ethical frameworks for autonomous systems and genetic engineering advancements

Qualifications

  • MSc or PhD in Futures Studies, Systems Thinking, or related field
  • 5+ years experience in strategic foresight or trend analysis
  • Proficiency in predictive analytics tools (e.g., Tableau, R) and simulation software
  • Published research on biotech or AI ethics (portfolio required)
  • Experience presenting to C-suite executives in Fortune 500 companies
  • Certification in Strategic Foresight (e.g., from AC/FS)
  • Deep understanding of Web3.0 and metaverse ecosystems

Required Skills

Strategic Foresight Trend Analysis Scenario Planning Quantum Computing Biotechnology Ethics AI Governance Systems Thinking Predictive Modeling

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