Backend (C#/.NET) Developer

Andersen is hiring a Backend (C#/.NET) Developer for a project developing insurance analytics solutions that support risk assessment, data-driven insights, and financial decision-making. The customer is a global organization operating in the professional services domain, providing advisory and analytical support across multiple industries. The project focuses on enhancing an insurance analytics platform that combines actuarial methodologies, machine learning, and advanced data analytics for risk management and financial decision-making.

• Proficient in software development using C# .NET for 3+ years.
• Experience with the full software development lifecycle in a commercial/production environment including requirements capture, design, implementation, testing, deployment, and maintenance.
• Knowledge of software engineering best practices: object-oriented design, design patterns, SOLID principles, Agile and Extreme Programming methodologies.
• Experience with SQL Server.
• English language proficiency from Upper-Intermediate and above.

Nice to have:

• Knowledge of Python.
• Experience with machine learning algorithms.
• Experience with desktop applications (WPF, WinForms).

• Primarily work on MLR desktop application focusing on Smart Search and component updates, and occasionally on other standalone tools owned by the team, involving math-driven tasks with machine learning algorithms.
• Collaborate with the Product Owner to define, refine, and deliver the product backlog.
• Design and document software solutions meeting functional and non-functional requirements.
• Implement and refactor product code in C# following best practices for maintainability, testability, and performance.
• Implement unit tests, develop test frameworks, and associated automated test cases.
• Review and debug code to identify defects, performance bottlenecks, or technical debt.
• Work closely with test engineers to ensure suitable test coverage and execute manual tests if necessary.
• Participate in sprint planning meetings, daily stand-ups, and sprint retrospectives to improve team velocity, processes, and engineering practices.
• Use AI to support development.

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