Executive, Group Corporate Assurance (Data Analytics)

This role is a junior/entry level Executive who has experience and/or competencies in internal audit and data analytics.

Key Responsibilities

• Data Extraction \& ETL:

Assist in extracting data from various systems and local databases; perform data cleaning and mapping to ensure consistency across the Group.

• Audit Support:

Collaborate with field auditors during the planning phase to identify high-risk areas using exploratory data analysis.

• Statistical Outlier Analysis:

Apply statistical techniques to identify instances that deviate significantly from the historical norms or benchmarks.

• Joint Reporting:

Partner with Lead Auditors to create "Data Stories"—using visualizations to help the operational team explain complex findings to Management.

• Communication:

Present analytical findings to the internal audit team, helping them understand what the data suggests about the subsidiary’s control environment.

Education \& Experience

• Education: Bachelor’s degree in Statistics, Data Science, Finance, Accounting, or Information Systems.
• Experience: 0–2 years of experience. A background in Audit Analytics, Data Science or Business Intelligence is a strong plus.
• Candidates possessing one or more of the following will be highly regarded: -
• \> Data Visualization: Microsoft Certified: Power BI Data Analyst Associate (PL-300) or equivalent Tableau Desktop Specialist.
• \> Programming: PCEP (Certified Entry-Level Python Programmer) or evidence of Python/R proficiency through a portfolio.
• \> Cloud Infrastructure: Microsoft Azure Data Fundamentals (DP-900) or Azure Fundamentals (AZ-900

).

Technical Skills

• SQL Proficiency: Ability to join complex tables and clean data from disparate data sources.
• Visualization: Skill in Power BI or Tableau—specifically creating "Exploratory Dashboards" that allow auditors to drill down into data and uncover trends and patterns.
• Excel Mastery: Advanced formulas and Power Query for quick data manipulation in the field.
• Python for Data Science: Proficiency in Pandas, NumPy, and Matplotlib/Seaborn for data cleaning, merging disparate subsidiary datasets, and performing statistical anomaly detection.

Soft Skills

• The "Detective" Mindset: A natural curiosity to find the irregularities in a sea of data.
• Active Listening: The ability to listen to an auditor’s manual process and visualize a way to automate it.
• Agility: Comfortable working in a fast-paced audit environment where priorities can shift based on what the operational team finds on the ground.
• Clear Communication: The ability to explain technical data results to a wide range of technical and non-technical audiences.