CTO / Head of Research – AI & Quantitative Asset Pricing

CTO / Head of Research – AI & Quantitative Asset Pricing

We are hiring a CTO / Head of Research to lead quantitative research and technology for ML-driven investment strategies. This is a combined role responsible for alpha research, research infrastructure, and production deployment, with direct ownership of translating academic ideas into live investment systems.

The role is suited for a senior quantitative researcher with deep expertise in machine learning, asset pricing, and financial markets, and experience operating in or close to hedge fund / systematic investing environments.

Responsibilities

Research & Alpha

• Lead research in ML / deep learning–based asset pricing and return forecasting.
• Design, validate, and oversee systematic trading and portfolio construction frameworks.
• Ensure research rigor: data handling, backtesting, validation, and risk controls.
• Own the research-to-production pipeline, including model handoff and monitoring.

Technology

• Define and own the research and production tech stack.
• Oversee data pipelines, research infrastructure, and live model deployment.
• Establish standards for reproducibility, versioning, and MLOps.
• Make architecture decisions balancing research flexibility and production stability.

Leadership & Collaboration

• Manage a small, high-quality team of quantitative developers and researchers.
• Lead collaborations with universities, PhD students, and academic researchers.
• Work directly with leadership on strategy, capacity, and risk.

Requirements

• PhD preferred in a quantitative field (Finance, Economics, CS, ML, Physics, Statistics).
• Senior experience in quantitative research, asset pricing, or systematic investing.
• Strong background in ML / AI, including deep learning applied to financial data.
• Proven ability to move research into production.
• Solid understanding of financial markets, asset pricing, and portfolio construction.
• Experience leading or mentoring small research or engineering teams.

Preferred

• Experience at a hedge fund or systematic asset manager.
• Track record of original research (academic or applied).
• Experience supervising or working with PhD researchers.
• Familiarity with institutional research and risk standards.

Tech Stack (Representative)

• Python (primary); optional C++ / Rust
• PyTorch / TensorFlow / JAX
• pandas, NumPy, SQL
• AWS, Docker, Terraform
• Research backtesting and model deployment pipelines

Industry

Quantitative Investment Management

Employment Type

Full-time