Lead Risk Analyst

3 days ago

Brackenfell, South Africa Shoprite Group Full time

**Purpose of the Job**:
The purpose of the Lead Risk Analyst role is to leverage Shoprite’s vast operational data to execute analysis with predictive modelling in order to shape tactical and strategic initiatives that drive risk mitigation, loss prevention, general assurance and overall customer centric experiences in-store. This includes optimising and integrating data with various in-store processes and financial models to define and enhance practices or identify opportunities. The role builds insights and/or tools that identifies risks across the value chain in all parts of the business, providing concrete inputs that guide the team to either enhance, slow down or stop activities based on the trajectory of data findings and forecasts. The role leads a specialised data science and analytics team and interacts with various cross-functional teams with a strong collaborative approach to achieving predictive models that provide assurance between the Finance, Loss Prevention and Audit functions.

**Job Objectives**:
**Qualifications**:
Essential Degree or diploma in Finance, Commerce, Computer Science or equivalent**
Experience**:
Essential 6+ years experience in a financial, or business context facilitating data analytics to guide business process or decision making. Extensive practical experience across the retail operations value chain, with demonstrated understanding of in-store retail operations and financial risk. Desirable Exposure to leading a small team of specialists to mitigate risks and build operational efficiencies.**
Knowledge and Skills**:
Essential Proficiency in MS Office 365 with advanced PowerPoint skills. Desirable Knowledge of legislation relevant to the collection, storage, and exploitation of customer data. Knowledge of data structures relevant to both operational and business intelligence systems. Strong report writing skills in Tableau software or similar. Strong understanding of data mining models, structures, theories, principles, and practices. Knowledge of Business Intelligence and Data Warehousing. Knowledge of AWS / cloud. Skilled in using the open-source statistical package R, Python, or similar. Skilled in using SQL in the data mining process, particularly for data preparation.**
Applicant Feedback Policy**:

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