Internal Audit Data Analyst

Mission

Within the Group Internal Audit and reporting to the Head of Audit Data Analytics, the Data Analyst contributes to the development of Data Analytics/AI tools to support Internal Audit’s core processes, including risk assessment, audit planning, audit execution, reporting, and follow-up.

Main responsibilities

• Designing and maintaining a robust, scalable, and secure data-processing environment (data collection, transformation, using ETL tools and/or code).
• Developing reusable analytical assets, including statistical models, scripts, and AI/machine-learning models to automatize audit testing procedures.
• Supporting the integration of analytical results into Internal Audit deliverables such as dashboards, automated reports, and analytical products for non-technical users.
• Collaborating with auditors and subject-matter experts to prioritize relevant audit use cases, translating audit objectives into analytical requirements and developing appropriate data-based solution.
• Maintaining documentation for existing solutions, analytical methodologies, data sources, and model development.
• Providing IT support for the administration and maintenance of audit management software.
• Building effective relationships with key stakeholders, including data owners, data governance and IT teams.
• Participating in data-related working groups and communities of practice across the Bank. Keeping up to date with technological developments.

Your Profile

• At least 3 years of relevant experience in data transformation and analysis within a medium-sized or large organization, preferably in banking or financial services.
• Master’s degree in Data Science, Computer Science, Applied Mathematics, Physics or a related field.
• Expertise in core data science programming languages (e.g. Python, R, SQL) and libraries (e.g. Scikit-learn, Seaborn, PyTorch, TensorFlow).
• Experience in using Generative AI and Large Language Models (LLMs) to develop and apply AI-drive solution and AI-assisted automation, including competences in designing and operationalizing AI and ML platforms and pipelines.
• Experience with the design and implementation of ETL data-processing workflows.
• Knowledge in applying descriptive and inferential statistics, data-quality techniques, and analytical testing methodologies.
• Experience with data-visualization tools, knowledge of Power BI is an advantage.
• Integrity, independence, intellectual curiosity, and a constructive, solutions-oriented mindset.
• Strong organizational skills and the ability to manage several projects simultaneously.
• Strong written and verbal communication skills, with the ability to adapt communication to technical and non-technical audiences.
• Versatility and adaptability required to work effectively within a small team of Data Analysts. Fluent in French and English, both written and spoken; additional languages are an advantage.

Others

Swiss Residence

Core Competencies : Adherence to the company’s values: Dedication, Conviction, Agility and Responsibility - Compliance with regulations and internal directives