Algorithm Engineer - Financial Services

Posted 14 Days Ago
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London, Greater London, England, GBR
In-Office
Entry level
Quantum Computing
The Role
Develop and evaluate classical algorithms and machine-learning methods for banking, fintech, payments, fraud detection, credit risk, and transaction modeling. Build production-relevant baselines and synthetic-data benchmarks, collaborate with quantum algorithm engineers, integrate methods into applications, and assess privacy, calibration, robustness, operational usefulness, and model-risk trade-offs. Communicate results and limitations to technical and non-technical stakeholders.
Summary Generated by Built In

At OQC, we aren’t just theorising about the future; we’re building it. Born from a philosophy of bold innovation, we’ve transitioned quantum computing from an academic ambition into a commercial reality—and we’re just getting started.

The Purpose

Apply your financial-services expertise to build practical algorithms and applications that bring classical and quantum computing together.

As our Algorithm Engineer - Financial Services, you’ll select, adapt and implement methods for banking, fintech and payments applications. Working alongside quantum algorithm engineers, you’ll help connect established approaches with emerging quantum capabilities and assess their practical value against strong classical alternatives.

Your focus will be on turning technical capability into useful applications, combining hands-on implementation with an understanding of what financial-services organisations need from their technology.

The Role

Working within our Product team and reporting to Product and Engineering leadership, you’ll be a senior, hands-on individual contributor collaborating across algorithm engineering, software and technical product development.

You’ll bring financial-domain knowledge to the team, helping select suitable methods, implement algorithmic components and integrate them into wider applications. Alongside this development work, you’ll contribute rigorous evaluation: understanding how methods perform, where their limitations lie and whether the results are meaningful in an operational setting.

This opportunity could suit someone already building algorithms into commercial applications, or a researcher whose work is closely connected to business needs and practical application. Previous quantum-computing experience is not essential.

The role is based in King’s Cross, London, with hybrid working and regular time together in the office.

What You’ll Be Working On

  • Select, adapt and implement classical algorithms and machine-learning methods for financial-services applications, including areas such as fraud detection, credit risk and transaction modelling.
  • Collaborate with quantum algorithm engineers and technical product colleagues to combine domain expertise with quantum and hybrid methods, helping integrate algorithmic components into useful applications.
  • Build strong, production-relevant classical detection and prediction baselines, enabling meaningful comparisons with quantum and hybrid approaches.
  • Define classical synthetic-data baselines against which quantum-generated data can be assessed.
  • Evaluate practical usefulness, privacy, calibration and robustness over time, considering operational requirements and customer acceptance.
  • Communicate findings, limitations and performance trade-offs clearly, helping the wider team make evidence-based decisions about the suitability of different approaches.

What We’re Looking For

Essential
  • Experience in quantitative research, applied science or algorithm engineering within banking, fintech or payments.
  • Strong expertise in one or more of fraud detection, anti-money laundering (AML), credit risk, market risk, transaction modelling, rare events or financial time series.
  • An understanding of operational metrics, model-risk requirements and the consequences of false positives and false negatives.
  • Hands-on experience implementing and evaluating algorithms or machine-learning methods, with a clear understanding of how your work supports practical financial-services needs.
  • The ability to take ownership, communicate clearly and collaborate effectively across technical and non-technical disciplines.
  • A degree or equivalent practical experience in quantitative finance, mathematics, computer science or a related discipline.
Desirable
  • Experience helping turn algorithms into commercially used applications or products. We also welcome relevant research experience where the work is closely connected to business users and their needs.
  • Experience working on enterprise platforms, data products or regulated customer deployments.
  • Familiarity with quantum computing or hybrid classical–quantum products.
  • A relevant professional or postgraduate qualification.

The ‘Nice-to-Haves’

  • A pragmatic approach to problem-solving, balancing technical rigour with practical delivery.
  • Curiosity about emerging technologies and their potential applications in financial services.
  • Comfort working in a fast-evolving technical environment, where approaches and products are still taking shape.

Why Join OQC

You’ll join a multidisciplinary team working at the intersection of financial services, software and quantum computing.

This is an opportunity to bring your existing expertise into an emerging area of product development, work alongside quantum specialists and help turn promising methods into practical applications. Your contribution will help establish not just what the technology can do, but how its value should be measured against the needs of financial-services users.

Skills Required

  • Experience in quantitative research, applied science, or algorithm engineering within banking, fintech, or payments
  • Strong expertise in fraud detection, anti-money laundering, credit risk, market risk, transaction modeling, rare events, or financial time series
  • Understanding of operational metrics, model-risk requirements, and false-positive and false-negative consequences
  • Hands-on experience implementing and evaluating algorithms or machine-learning methods for practical financial-services applications
  • Ability to take ownership, communicate clearly, and collaborate across technical and non-technical disciplines
  • Degree or equivalent practical experience in quantitative finance, mathematics, computer science, or a related discipline
  • Experience turning algorithms into commercially used applications or products
  • Relevant research experience connected to business users and practical needs
  • Experience with enterprise platforms, data products, or regulated customer deployments
  • Familiarity with quantum computing or hybrid classical-quantum products
  • Relevant professional or postgraduate qualification
  • Pragmatic problem-solving approach balancing technical rigor with practical delivery
  • Curiosity about emerging technologies and financial-services applications
  • Comfort working in a fast-evolving technical environment
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The Company
HQ: Reading
129 Employees
Year Founded: 2017

What We Do

Quantum computing is poised to reshape our world by addressing the complex challenges we face today. We deliver enterprise-ready quantum solutions that will empower humanity with quantum capabilities, paving the way for a brighter future.

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