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Operate live sports trading systems, monitor betting and prediction markets, identify inefficiencies, and support trading strategy optimization. The role provides real-time feedback to developers and quantitative analysts, collaborates with operational support, and resolves issues to minimize downtime and risk. Applicants need analytical ability, betting-market knowledge, precise execution, and willingness to work day, evening, weekend, and overnight shifts.

Manage a betting-market trading system to maximize trade volume and meet performance targets. Collaborate with developers, quants, and operational support teams to improve the trading pipeline, provide practical system feedback, and resolve issues quickly to minimize downtime. The role requires availability for day, evening, weekend, early morning, and late-night shifts, along with a strong interest in data, betting markets, and quantitative analysis.

Develop mathematical and statistical models, high-performance algorithms, data processing pipelines, and betting-operation automation. Acquire, clean, analyze, and interpret complex datasets; produce reports; identify trends and process improvements; and build, test, and deliver software. The role also involves back-testing, simulations, and collaboration with mathematicians, data scientists, and software engineers.

Develop and optimize cloud-based, low-latency trading systems processing real-time market and event data. Responsibilities include building data pipelines, integrating trading platforms, improving trading strategies, developing analytical reporting, optimizing millisecond-level performance, collaborating with quantitative analysts, and maintaining GCP infrastructure and deployment pipelines.

Identify inefficient manual processes across business teams and design, build, test, deploy, and maintain reliable automation solutions. Collaborate with technical and non-technical stakeholders, use programming languages, APIs, workflow tools, data processing, and AI, and measure automation impact. Own projects from discovery through implementation while documenting solutions, monitoring reliability, gathering feedback, and continuously improving workflows.

Develop advanced automation and visual data processing workflows using AI tools, focusing on computer vision and data streaming techniques while ensuring system reliability and scalability.

Develop and maintain low-latency football data acquisition and analysis systems using social media and other unstructured sources. Build relational database schemas and RESTful API integrations for modeling and trading systems, optimize system performance, and integrate LLM-based pipelines that convert unstructured data into structured outputs. Collaborate with football analysts to ensure data quality and utility.

Operate and monitor live sports trading systems, execute trades to meet performance targets, identify market inefficiencies, provide real-time feedback to developers and quants, troubleshoot issues, and help optimise the trading pipeline across shifts.

The Senior Software Developer will design, develop, and optimize cloud-based low-latency data processing systems while collaborating with analysts to implement trading strategies.

Develop, backtest, operationalise and trade American Football quantitative strategies (pre-match and in-play). Set and adjust pricing, monitor models live, manage risk, collaborate with quants and engineers, and support data acquisition and cleaning.