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Cooper Fitch

Cooper Fitch

cooperfitch.ae

1 Job

94 Employees

About the Company

Since 1997, Cooper Fitch has been a leader in recruitment and executive search, serving the Middle East with unparalleled expertise and dedication. We find, build, and retain outstanding leaders and teams that drive transformational change and exceptional growth for our clients. Specialising in recruitment and executive search, human resources advisory services (HRAS), and tailored recruitment solutions such as recruitment process outsourcing (RPO), we are committed to attracting, developing, and retaining the best talent.

With our deep understanding of the industries we serve, we are experts in discovering and nurturing leaders who make a significant impact. Our ethos, "A meeting of minds," captures our dedication to forming connections that inspire people, unleash talent, and transform organizations to build better futures together.

Cooper Fitch is a proud member of the Talent Club, a global network with 35+ offices across four continents.

For more information about how Cooper Fitch can support your organisation’s growth and leadership needs, visit our website or contact our offices directly.

Opening hours:
Monday- 08:30- 17:30
Tuesday- 08:30- 17:30
Wednesday- 08:30- 17:30
Thursday- 08:30- 17:30
Friday- 08:30- 14:00
Saturday- Closed
Sunday- Closed

Listed Jobs

Company background Company brand
Company Name
Cooper Fitch
Job Title
Head of Applied AI – Investments
Job Description
**Job Title**: Head of Applied AI – Investments **Role Summary** Lead the design, development, and deployment of end‑to‑end AI/ML systems that drive alpha generation, portfolio construction, and risk analytics across a global investment platform. Build and scale a world‑class Applied AI & Quant research team, bridging deep technical expertise with strategic investment decision‑making. **Expectations** - Build and commercialize production‑grade AI/quant systems that influence multi‑billion dollar investment decisions. - Establish a modern, scalable quant + AI research platform with cutting‑edge methods (LLMs, agentic AI, advanced quant techniques). - Deliver high visibility and measurable impact on senior leadership strategy. - Foster a culture of innovation, rigorous engineering, and continuous learning. **Key Responsibilities** 1. **Platform Architecture & Engineering** – Design and own the end‑to‑end AI/ML pipeline from data ingestion to model deployment, ensuring scalability, robustness, and compliance. 2. **Alpha & Risk Research** – Lead research initiatives that uncover trading signals, refine portfolio construction algorithms, and enhance risk analytics tools. 3. **Decision‑Support Development** – Build real‑time decision‑support dashboards and AI‑driven recommendation engines for investment teams. 4. **Team Leadership** – Recruit, mentor, and grow a high‑performance team of AI/quant engineers, researchers, and data scientists. 5. **Stakeholder Collaboration** – Translate technical insights into actionable investment strategies in partnership with portfolio managers and senior executives. 6. **Governance & Compliance** – Ensure all AI/ML models meet regulatory standards, ethical guidelines, and risk controls. 7. **Innovation Management** – Evaluate and pilot emerging technologies (LLMs, reinforcement learning, automated agents) and integrate them into the investment workflow. **Required Skills** - 15+ years of senior leadership in quantitative research, AI/ML, or data science within investment environments (hedge funds, asset managers, private equity). - Proven track record of building and deploying production‑grade AI/quant systems that deliver alpha and risk insights. - Deep expertise in machine learning frameworks (TensorFlow, PyTorch, JAX), large‑language‑model development, reinforcement learning, and probabilistic modelling. - Strong quantitative and financial knowledge covering portfolio theory, risk modelling, and factor analysis. - Leadership skills: team building, cross‑functional collaboration, strategic thinking, effective communication of technical concepts to non‑technical stakeholders. - Experience with cloud infrastructure, data engineering, and DevOps pipelines for ML lifecycle management. - Understanding of financial regulations, compliance, and ethical AI practices. **Required Education & Certifications** - Advanced degree (PhD or Master) in Computer Science, Electrical Engineering, Mathematics, Quantitative Finance, or a related field. - Optional professional certifications: CFA, FRM, or recognized AI/ML credentials (e.g., TensorFlow Developer, Microsoft Certified: Azure AI Engineer, etc.).
New york, United states
On site
18-03-2026