Requirements
* Advanced proficiency in software development
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* Experience building and shaping large systems in complex business domains
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* Experience building robust systems where the 'product' is high-quality data and you can 'speak the language' of analysts and data scientists
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* Confidence to work closely with partners from other disciplines to challenge assumptions and discover underlying problems
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* Demonstrable leadership skills: you have mentored juniors and inspired teams to deliver cross-functional projects. You can balance hands-on coding with strategic planning
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* You use AI (like Cursor, Claude Code or similar) in your daily flow—whether for work or for fun. You use it to blast through boilerplate and research, so you can focus on the hard parts: complex architecture, rigour, and high-stakes decision-making
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* (Desirable) A strong numerical or technical background, ideally with a degree in physics, engineering, maths, computer science or a related field
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* (Desirable) Experience building and maintaining analytics systems
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* (Desirable) Experience with Python, Snowflake, or PostgreSQL
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* (Desirable) Experience working on feature-management systems such as feature services or features stores
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* (Desirable) An understanding of complex data systems, including event-sourced data models
What the job involves
* As Tech Lead, you’ll be responsible for the engineering systems that underpin Credit Risk modelling at iwoca
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* You’ll focus on the platform, pipelines, and production systems around the models, rather than building models yourself
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* This is a hands-on technical leadership role, combining technical direction, line management, and individual contribution
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* Lead four engineers working on the modelling platform and surrounding systems; help the team deliver high-quality solutions
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* Raise engineering standards across modelling systems and infrastructure, with a focus on reliability, observability, reproducibility, and safe change
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* Set technical direction by understanding adjacent systems, workflows, and constraints to identify the right problems to solve at the right time
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* Stay hands-on in the codebase, especially when the team is dealing with ambiguity, cross-system complexity, or problems without an obvious owner
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* Lead by example in how problems are approached and how rigour is balanced with speed of delivery
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* Contribute directly to the systems that matter most, making pragmatic changes that reduce friction, strengthen the platform, and improve reliability in production
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* Engineering decisions in this area directly affect the accuracy of our credit decisions and the volume of lending iwoca can responsibly support
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* Better infrastructure leads to faster experimentation and better models
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* Help the team to work faster and with more confidence in the platform. Work with data scientists and strategy analysts to maintain the feedback loop between analysis, strategy and engineering
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