My client, a stealth-mode quantum fintech venture , backed by a leading global financial institution, is on a mission to transform the future of quantitative analytics. By combining breakthroughs in quantum computing, AI, and machine learning with deep financial domain expertise, we are building next-generation applications that will redefine performance in financial services.
As Chief Scientific Officer (CSO) , you will spearhead our scientific strategy, leading advanced research and innovation while ensuring that cutting-edge discoveries translate into commercial impact.
Key Responsibilities :
- Lead end-to-end research, design, and implementation of quantum, quantum-inspired, and advanced machine learning algorithms to power high-performance financial applications.
- Conduct deep research into both classical and quantum computing approaches , identifying opportunities for disruptive improvements.
- Provide strategic direction to guide the company’s research agenda in quantum technologies, AI, and quantitative finance .
- Collaborate with the CTO to integrate algorithmic advances into the platform and applications.
- Stay at the forefront of developments in gate-based quantum computing, adiabatic quantum computing, variational algorithms, QUBOs, tensor networks, quantum machine learning, quantum simulations, Fourier transforms, simulated annealing, and other optimisation techniques .
- Tune and optimise applications to ensure peak performance across a variety of quantum hardware back-ends and middleware environments .
- Design and develop proof-of-concept prototypes that showcase algorithmic and hardware-driven advances.
- Publish selected research and thought leadership, while protecting IP through patents and legal frameworks.
- Evaluate emerging technologies and strategic partners in the quantum technology ecosystem (hardware providers, middleware, and software platforms).
- Ensure strategic alignment with commercial priorities while fostering collaboration across teams and with other C-level executives.
Ideal Candidate :
- 10+ years in cutting-edge research across computer science, quantum computing, and applied machine learning , with at least 2+ years in a professional or commercial research setting.
- Deep expertise in quantum algorithms and applications , including both gate-based and adiabatic approaches .
- Broad knowledge of algorithmic methods: supervised/unsupervised machine learning, neural networks, transformers, tensor networks, evolutionary algorithms, PDEs, Monte Carlo simulations, discrete/continuous optimisation, and beyond.
- Strong track record of publications in high-impact journals and experience leading research-to-commercialisation initiatives.
- Financial services exposure (e.g., trading, fraud detection, risk management) is highly valuable.
- Entrepreneurial mindset with the ability to balance academic innovation and commercial application in a fast-paced fintech environment.
- Proven leadership skills and the ability to communicate complex concepts to both technical and non-technical stakeholders.
