Job Description

What you\'ll be doing: The Analytics Manager will be responsible for a variety of activities ranging from data analysis, data modelling, process automation and training. Data Extraction and Cleansing (xxx% of Role) Lead the process of data extraction and analysis from various financial systems Query and organize large datasets to understand underlying schema and relationships. Apply profiling and data quality validation on large datasets and document necessary business rules for transformation. Knowledge of various methods/tools used for ETL. Data Analytics (xxx% of Role) Present audit insights in a user-friendly intuitive way to business stakeholders. Assist in defining data requirements, design, and execution of audit insights. Develop analytics solutions to support the team during operational, financial and project audits. Design and develop predictive and prescriptive data insights to optimize operational efficiencies and mitigate risks. Create dynamic data visualization and risk monitoring dashboards. Construct complex data models to detect anomalies and patterns using statistical models. Leverage a risk-based approach to detecting engagements with high volumes of data and complex filtering criteria. Deliver timely results in fast evolving audit projects. Recommend industry best- practices on Audit Data Analytics and push for continuous improvement of automation. Identify automation opportunities and develop solutions that simplify audit processes to make WPP IA more efficient. Training (xxx% of Role) Promote the use of audit analytics and assist in training team members. Support team members in adopting automation across all phases of the audit process. Enhance the team\'s digital capabilities by launching a dedicated training program. Assist auditors during stakeholder interviews by preparing reports on the go. Serve as the SME in areas of business intelligence and analytics. Bachelor\'s degree in the advanced field of technology or in a related discipline such as Mathematics/ Statistics/Data Analytics 5+ years of professional work experience as a Data Analyst, Data Engineer, Data Scientist or comparable. Experience in Auditing is preferred, but not required. Strong analytical problem-solving skills including experience with mining large datasets (e.g., SQL, ACL) Experience with standard data science programming languages (e.g., Python, R) Hands-on experience with BI/visualization tools (e.g., MicroStrategy, Power BI, Tableau) Experience with reporting and dashboarding skills (e.g., JavaScript, HTML, CSS) would be nice to have. Knowledge of anti-fraud, investigations, anti-bribery and corruption and regulatory requirements will be an added advantage.

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