Principal Quant Engineer

Location: GBR - London, Canada Square

Remote Type: Hybrid (8 days/month)

Time Type: Full time

Job Description

Join us at Wolters Kluwer and be part of a dynamic global technology company that makes a difference every day. We’re innovators with impact. We provide expert software and information solutions that the world’s leading professionals rely on, in the moments that matter most.

As part of this mission, we’re looking for a driven and experienced Principal Quant Engineer to join our team.

About the role:

We are looking for a quantitative modelling specialist with software engineering skills to design, build, and operationalise advanced models in environmental domain, with a particular focus on air quality and environmental metrics.

This role sits at the intersection of quantitative modelling, software engineering, and applied AI. You will work on production-grade models that inform decision-making, forecasting, risk assessment, and optimisation, embedding them into scalable software systems rather than one-off analyses.

Key Responsibilities:

Quantitative Modelling

• Design, implement, and validate quantitative models for environmental and air quality metrics (e.g. emissions, dispersion, exposure, compliance indicators)
• Translate scientific, regulatory, or financial concepts into robust mathematical and statistical models
• Perform sensitivity analysis, uncertainty quantification, and model validation
• Document assumptions, methodologies, and limitations clearly for technical and non-technical stakeholders

Software Engineering

• Build production-ready model implementations, not just notebooks or prototypes
• Develop scalable, testable, and maintainable codebases
• Integrate models into backend services, APIs, or data pipelines
• Collaborate with platform and product engineers to deploy models into live systems
• Ensure performance, reliability, and reproducibility of model outputs

AI & Advanced Analytics

• Apply machine learning and AI techniques where appropriate (e.g. regression, time-series, probabilistic models, optimisation, LLM-assisted analytics)
• Combine deterministic models with data-driven approaches
• Use AI responsibly with clear explainability and governance, especially in regulated or high-impact contexts
• Stay current with advances in applied AI relevant to modelling and decision systems

Collaboration & Stakeholder Engagement

• Work closely with product managers, domain experts, and engineers to shape modelling requirements
• Explain complex models and results to non-specialist audiences
• Contribute to technical design discussions and architectural decisions

Required Experience & Skills:

Quantitative & Domain Expertise

• Strong background in quantitative modelling, mathematics, statistics, physics, engineering, economics, or a related field
• Demonstrable experience building: Financial models and/or, Environmental or air quality–related models (e.g. emissions, atmospheric data, environmental indicators)
• Experience working with real-world, noisy, incomplete datasets

Software Engineering

• Strong programming experience in Python (required) or C#
• Experience with software engineering best practices: Version control (Git), Testing frameworks, Code reviews, CI/CD (desirable)

AI & Data Tooling

• Practical experience with machine learning libraries (e.g. scikit-learn, PyTorch, TensorFlow)
• Experience using AI models as part of analytical or decision-making workflows
• Understanding of model evaluation, drift, and performance monitoring
• Experience combining traditional modelling with AI techniques is highly valued

Nice to Have:

• Experience with time-series analysis and forecasting
• Knowledge of environmental or financial regulations and reporting standards
• Experience with geospatial data, sensor data, or remote sensing
• Exposure to MLOps or model lifecycle management
• Experience working in SaaS or product-led organisations

What We’re Looking For (Mindset):

• Someone who enjoys building models that actually run in production
• Comfortable bridging theory and engineering
• Pragmatic about model complexity vs business value
• Curious, detail-oriented, and rigorous
• Able to work independently while collaborating effectively with cross-functional teams

If you think that you have the needed requirements click on the apply button to join us and be the difference. If making a difference matters to you, then you matter to us.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, disability, or any other protected status, in accordance with local regulations.

#LI-Hybrid

Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.