Global Head of Insight Generation and AI Adoption, Managing Director
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- Hangzhou, Zhejiang
- Permanent
- Full-time
- Support SSIM’s AI vision and strategy; lead end‑to‑end implementation of data science capabilities, AI frameworks, tooling, and vendor adoption across all business lines.
- Lead and mentor high‑performing AI teams across the US, China, India, and Poland—building a culture grounded in deep AI expertise and accountability (not traditional staff‑augmentation models).
- Define SSIM’s AI architecture, establish enterprise AI standards, and guide implementation and governance practices.
- Ensure a modular, scalable, and reusable AI architecture to eliminate siloed development and accelerate time to market.
- Champion engineering excellence, technical rigor, and innovation across the organization.
- Innovation & Best Practices: Evaluate, adopt, and standardize cutting‑edge AI capabilities—including Agentic AI, Generative AI, and foundational AI/ML/DL models.
- Quality & Performance: Ensure solutions meet the highest engineering standards through code reviews, testing frameworks, and adherence to industry guidelines.
- Collaboration & Mentorship: Build a collaborative engineering community focused on continuous learning, knowledge sharing, and professional development.
- Scalability & Resilience: Architect systems capable of supporting global business workloads with strong reliability and performance characteristics.
- Security & Compliance: Uphold stringent risk, security, and regulatory requirements; ensure robust data protection and governance.
- Lead global AI core teams with a focus on innovation, delivery excellence, and operating leverage.
- Manage major vendor relationships—including AI platform providers and service partners—ensuring strong integration, service quality, and contractual outcomes.
- Oversee the full AI/ML model lifecycle from ideation to production deployment across a diverse set of use cases and global users.
- Master’s degree required (Computer Science, Financial Mathematics, or related field); PhD preferred.
- 15+ years in the asset management industry, with deep knowledge of asset management, public and private markets, and distribution/sales.
- 10+ years hands‑on AI experience with a strong track record delivering AI solutions and platforms.
- Proven experience leading global technology organizations across product, data, AI, and engineering domains, with strong delivery execution.
- Strong understanding of the AI vendor landscape and demonstrated experience adopting vendor products and open‑source frameworks to improve scale and growth.
- Exceptional leadership, stakeholder management, communication, and relationship‑building skills.
- Demonstrated ability to translate complex business needs into scalable, user‑centric technology solutions.
- Fluent in English; highly detail‑oriented, results‑driven, candid, and execution‑focused.
- Prior data science development and management experience in large financial institution.
- CFA or equivalent credential.