Data Visualization

Job Purpose

The IsDB Internal Audit Department (IAD) team is passionate about defining and executing IAD activities that drive technology solutions fit for high-performing internal audit functions, implement data analytics (e.g., NLP, ML, RPA) and data visualization at scale; maintain an information technology systems environment consistent with the highest standards, explore emerging technology or continuous process improvements that enhance IAD's operations, and advise IAD leadership on the information technology and digital transformation (cost/benefit investment decisions and use cases) to achieve IAD's Strategy.

The Data Visualization and Analytics Expert is responsible for providing analytical support to Audit Specialists, primarily in the execution of assurance and advisory services. He shall be experienced in Analytics, Data Processing, Modelling, Cleansing, and Data Mapping. He will provide advanced data analytics through the use of technology scripting, development, configuration of programs, and integration of systems. Also, contributes actively to the formulation of engagement strategies, approaches, and recommendations to improve efficiency, effectiveness, and internal controls.

Key Accountabilities
**Audit Planning and Execution**
- Contributes to the planning and execution of complex audits and advisory services through advanced data analytics.
- Develop continuous Audit Programs (including scripts and algorithms) based on the automation of the projects already done on data mining and process mining.
- Participate in the preparation of the yearly Audit plan and collaborate with the audit team to plan and develop audit activities.
- Contribute to Implementing the audit plan by conducting relevant audit procedures for the required audit engagement.

**Data Management and Access**
- Facilitate access to relevant data warehouses.
- Effectively coordinate the communication of data requirements to stakeholders in and outside of IAD for a Cloud first-environment, with robust data pipelines, and fit-for-purpose Artificial Intelligence models.

**Data Visualization and Reporting**
- Create data visualizations and analytical reports that promote understanding of key insights for a diverse range of audiences.

**Process Mining and AI Implementation**
- Design, Implement, run, and maintain Process Mining programs or activities using Process Mining Software (e.g., Celonis Intelligent Business Cloud).
- Introduce Artificial Intelligence adapted to Internal Audit in the Internal Audit Department by starting to adopt innovative technologies such as: Machine Learning, Deep Learning and Natural Languages Processing, and computer vision technologies.

**Tools and Software Management**
- Manage and maintain IAD's Computer Assisted Audit Tools Software (TeamMate+, ACL, Celonis, Signavio), Websites (SharePoint), and Dashboards (Power-BI).

**Knowledge Sharing and Capacity Building**
- Share knowledge to contribute to increasing the auditors' use of data analytics.

**Reporting and Communication**
- Contribute to the preparation of a concise and informative audit report to effectively communicate the findings and recommendations to the relevant functions and senior management.

**Relationship Management**
- Develop and maintain effective and professional working relationships with all levels of staff within the organization, including Senior Management and Audit Committee of the Board.

**Special Assignments and Investigations**
- Assist in any special audit assignments or investigations mandated by the management.

Academic and professional qualifications
- Bachelor's degree in Information Technology, Data science, Big Data Engineer/Architect applied Mathematics, Economics, Statistics, Finance, or related field of study with a strong quantitative and computational background, preferably with advanced training. (mandatory)
- Professional Certification related to Data Science, Artificial Intelligence, Machine Learning, and Business Intelligence Development (preferred)
- Prior audit experience is preferred.
- Minimum five years of experience, with at least two (2) years of relevant experience in data management and analysis. (mandatory)
- Experience with database systems and data-warehousing, paired with demonstrated knowledge of leading data science practices, e.g., data acquisition, exploration, pipeline management, cleaning and feature engineering, modeling, and communicating results. (preferred)
- Experience using algorithms (NLP and ML are key, deep learning is a bonus), and data analysis and visualization tools such as Python and Power BI, Azure Cognitive Services, and Power Automate platform. (preferred)
- Experience in finance, information technology, or related fields in financial institutions or large organizations. (preferred)
- Familiarity with development banking operations and risk management, or similarly complex mission-driven global organizations would be an asset. (Good to have)
- Experience with