QA Data Analyst Full-Time 2024

Responsibilities
Execute QA Audit Plan to ensure NJV service quality SOPs are followed
Define and execute the digital testing strategy to identify risks and drive the testing coverage within the audit cycle to assess internal control activity, operational efficiencies and compliance with selected policies, procedures and Regulations.
Review the business process maps for each audit to identify the key automated business controls and critical data elements, and whether there are control gaps in the end to end flow.
Work with Product owners and IT stakeholders to prioritize backlogs, deliver solutions through environments and into production.
Sales and commercial audit
Set up a data model to test sales and commercial audits.
Develop a tool to identify wrong behaviors compared to Sales processes.
Bring the method into the actual sales process to detect wrong behaviors.
Report and find the root cause for the problem.
Propose solutions
Apply a systematic, risk-focused, disciplined, and balanced approach to evaluate and improve the effectiveness and efficiency of processes, internal controls, risk management and governance processes.
Drive innovation and technological improvements that support the activities of Internal Audit such as Data Analytics, Process and Data Mining
Others
To plan and execute initiative projects, together with cross-departments.
Assist in the identification, selection, and implementation of tools, technologies, and practices that support the overall QA process.
Requirements
Minimum of 1 year of experience in data analysis, specifically in data quality analysis, preferably in the logistics industry.
Proficiency in programming languages such as SQL and Python, with a focus on data analysis and manipulation in a logistics context.
Familiarity with statistical methods and tests relevant to the logistics industry, such as regression analysis, forecasting, and optimization.
Experience with statistical packages such as Gsheet, MS Excel, tailored for logistic data analysis.
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