Overview
In this role you will lead advanced optimisation projects and shape scalable ML architectures to improve payment flows. You’ll work with a team of data scientists to design decisioning systems that balance complex business objectives. Expect to translate data insights into robust, production-ready models and collaborate with product partners to drive impact at scale. This is a fast-moving role with opportunities to influence fintech solutions and data-driven .
Pay / Benefits
- hybrid working model
- flexible in-office schedule (three days per week)
- growth opportunities
- collaborative culture
- impactful work in fintech
- global team exposure
Responsibilities
- Lead projects and architecture design for multi-objective optimisation and scalable models
- Create custom loss functions, evaluation, and tuning frameworks for complex business problems
- Collaborate with product stakeholders to align technical strategy with business goals
- Apply efficient data transformations using distributed computing (e.g., Spark, Dask) and ensure robust test coverage for production systems
- Mentor junior team members and utilise model explainability methods to drive feature performance improvements
Key requirements
- 5+ years of experience designing, building and maintaining ML models for large-scale problems
- Deep understanding of frequentist and Bayesian statistics; supervised and unsupervised techniques
- Experience modelling complex interactions (e.g., cluster or network effects)
- Expertise in model explainability and feature engineering
- Proficiency in high-quality production-grade Python code and cross-functional collaboration
- Experience leveraging LLMs for coding support and process optimisation
- Strong communication skills tailored to broad audiences
- Proven ability to build trusting relationships with product stakeholders and understand business models
- collaboration with cross-functional teams
- mentoring junior members
- clear technical communication
- Spark
- Dask
- Python production-grade code
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