Job Description
Innovatech Solutions Inc. is seeking a visionary 2026 Futurist Strategist to shape our next decade of growth. As a key member of our executive strategy team, you'll decode emerging technological, societal, and economic trends to transform them into actionable business strategies. This role requires a rare blend of analytical rigor and creative foresight to position Innovatech at the forefront of innovation.
You'll collaborate with C-suite executives to develop long-term roadmaps while identifying disruptive opportunities across AI, quantum computing, and biotechnology. The ideal candidate thrives at the intersection of technology and human behavior, using data-driven insights to navigate uncertainty and build competitive advantages.
Responsibilities
- Analyze emerging global trends (2025-2030) across technology, geopolitics, and social behavior to inform strategic planning
- Develop scenario-based frameworks for market disruption and competitive positioning
- Lead cross-functional innovation workshops with R&D, product, and marketing teams
- Present foresight reports to executive stakeholders and board members with actionable recommendations
- Monitor patent landscapes, startup ecosystems, and academic research for breakthrough opportunities
- Integrate future-proofing principles into product development lifecycles
- Build and maintain a proprietary trend intelligence database with predictive analytics
Qualifications
- Advanced degree in Strategic Foresight, Technology Forecasting, or related field (PhD preferred)
- 7+ years in strategy consulting, corporate innovation, or futurism roles
- Proven track record of trend analysis with measurable business impact
- Expertise in scenario planning, Delphi methods, and horizon scanning
- Deep knowledge of exponential technologies (AI, quantum, synthetic biology)
- Exceptional communication skills with executive presence
- Portfolio published in foresight journals or industry whitepapers
- Experience with data visualization tools (Tableau, Power BI) and predictive modeling