Tech Lead – Advanced Analytics

Education

• Master's degree in Computer Science, Software Engineering, Mathematics, Physics, Engineering or related technical discipline.

Experience

• Minimum 6 years of professional experience in software development, data science or related fields, including experience acting as a technical lead or senior technical contributor on complex software products.
• Experience deploying, operating and maintaining analytical or machine learning solutions in production environments.
• Experience working in Agile product teams within complex enterprise environments.
• Experience working in the energy trading industry, particularly in power markets, would be considered an advantage.

Technical Skills

• Expert-level proficiency in Python and experience building production-grade backend applications.
• Strong experience designing cloud-native applications and distributed systems on AWS.
• Strong understanding of software architecture, design patterns, API design and system integration.
• Experience designing RESTful APIs and event-driven architectures.
• Experience with containerization technologies such as Docker and orchestration platforms including Kubernetes and ECS.
• Experience implementing CI/CD pipelines and Infrastructure as Code.
• Solid understanding of relational databases, SQL, data modelling and modern data platform architectures.
• Hands-on experience with Databricks, MLflow or comparable modern data and MLOps platforms.
• Strong knowledge of software engineering best practices, including automated testing, code reviews, observability and production support.
• Familiarity with Lakehouse architectures and modern Data Engineering practices would be an asset.
• Experience developing modern frontend applications and data visualization tools using React, or similar frameworks, would be considered a plus.

Skills

• Excellent communication and stakeholder management skills, with the ability to interact effectively with both technical and quantitative audiences.
• Strong analytical and problem-solving capabilities.
• Demonstrated ability to mentor engineers and provide technical leadership through influence.
• Ability to work effectively in a fast-paced, collaborative and international environment.
• Strong commitment to engineering excellence and continuous improvement.

Additional Information

Preferred qualifications include:

• PhD in Computer Science, Mathematics, Physics, Operations Research, Machine Learning, Artificial Intelligence or another quantitative discipline.
• Understanding of European energy systems, electricity markets and quantitative trading workflows.
• Experience with forecasting, optimization, time-series analysis or other quantitative modelling techniques, together with an understanding of the challenges involved in bringing analytical models into production.
• Experience building data-intensive or AI-enabled platforms supporting quantitative research.
• Knowledge of MLOps best practices, including model lifecycle management, model versioning, reproducibility, monitoring and governance.
• Experience leveraging AI-assisted software development tools (e.g. GitHub Copilot, Claude Code, Codex or equivalent) to improve engineering productivity while maintaining high standards of software quality.