Qubitra
Quantum Algorithms Scientist
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About The Company
We are a fast-growing startup at the intersection of quantum computing and financial services, applying cutting-edge technology and innovative solutions to solve complex business problems for our clients.
Our mission is to deliver real-world impact through high-quality product development, operational excellence, and strategic client engagement. We value collaboration, curiosity, and ownership, and are building a team that thrives in a fast-paced, high-growth environment.
About The Role
As a foundational scientific hire, you will shape the algorithmic direction of the company. You will conduct deep research into classical and quantum algorithms, design hybrid quantum–classical methods, and prototype new approaches relevant to financial institutions.
You will take ownership of algorithmic development in areas such as algorithmic trading, market making, risk analytics, derivatives pricing, and fraud detection.
This role is ideal for someone who is driven by mathematical elegance, scientific depth, and the ambition to translate quantum research into real-world, commercially meaningful solutions.
Key Responsibilities
Quantum & Classical Algorithm Research
- Design, prototype, and benchmark quantum algorithms for finance: QML, variational circuits, simulators, quantum optimization (QUBOs, annealing), quantum Monte Carlo, PDE solvers, and quantum-enhanced signal-processing models.
- Explore frontier areas including QML, hybrid workflows, error mitigation, advanced compilation, and noise-resilient optimisation.
- Conduct foundational research in quantum information, spectral methods, TDA, tensor networks, Fourier transforms, complexity theory, and related mathematical frameworks.
- Identify, develop, and test quantum and hybrid algorithms that work on near-term quantum hardware (NISQ).
- Evaluate and integrate existing AI/ML models where appropriate rather than reinventing from scratch.
- Analyze algorithmic performance, scalability constraints, and robustness to noise.
- Produce high-quality research notes, white papers, and internal memos guiding product strategy.
- Work with engineering and product partners to translate research into platform features.
- Contribute to high-impact publications, technical blogs, or conference papers.
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Required Experience
- MSc or PhD in Mathematics, Physics, Computer Science, Quantum Computing, or related fields. Preference for deep theoretical domains: differential geometry/topology, topological data analysis (TDA), spectral analysis, information theory, quantum physics/computing.
- Strong understanding of quantum mechanics, quantum circuits, qubit systems, and advanced quantum computing concepts.
- Solid knowledge of ML theory, optimization, Monte Carlo methods, Fourier transforms, neural networks, and algorithmic complexity.
- Hands-on experience with at least one quantum programming framework.
- Fluency in Python, vectorization and scientific computing libraries (NumPy, SciPy, Pandas).
- Ability to reason rigorously, communicate research clearly, and tackle open-ended scientific problems.
- Passion for the intersection of mathematics, AI, and quantum computing.
- Management of supervisory experience.
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Ideal Experience
- Research publications or open-source contributions.
- Experience with financial modelling, risk analytics, or quantitative methods.
- Understanding of optimisation theory (linear/non-linear, continuous/discrete).
- Familiarity with hybrid architectures, variational methods, and tensor networks.
- Some exposure to production systems or data engineering is a plus but not required.
By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.
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