Primary responsibilities:

• Develop and implement software applications that automate and optimise financial processes, enhancing efficiency and mitigating risks.
• Collaborate with business stakeholders and technical colleagues to identify areas for process improvement and design technical solutions that align with business objectives.
• Leverage data science and analytics expertise to extract actionable insights and support data-driven decision-making.
• Work closely with cross-functional teams, including the tech team, to architect and deploy solutions that fulfil business requirements and strategic goals.
• Communicate complex technical concepts effectively to non-technical stakeholders, including business leaders and external partners.

Technical Expertise:

• Proficiency in Python is required; familiarity with additional programming languages such as Java, C++, Go, Rust, and others is a plus.
• Strong understanding of software architecture patterns, including microservices and event-driven architecture.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerisation technologies like Docker, along with orchestration tools such as Kubernetes.
• In-depth knowledge of software development lifecycle methodologies, with hands-on experience in DevOps practices and CI/CD pipelines.
• Familiarity with frontend technologies, including React, Next.js, and JavaScript.
• Understanding of data science and analytics techniques, including machine learning and statistical modelling.
• Experience with integrating open-source machine learning platforms.
• Knowledge of how to design and implement data pipelines for efficient data processing and integration.
• Experience with database management systems, encompassing both relational and NoSQL databases.

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