Objectives of the position:
Data Analyst plays a critical role in driving continuous improvement, operational efficiency, and waste reduction across APAC and serves as the in-house expert for deriving actionable insights from Operations and Product management data to drive operational efficiency and support business decision-making. The analyst understands Operations and Product management data, requirements, gathers and consolidates data across APAC region, and distills this information into concise, actionable insights that can be effectively communicated to management and other stakeholders.
Key Responsibilities
- Develop clear and compelling visualizations to effectively communicate complex data insights to both internal and external stakeholders, enabling informed decision-making.
- Provide detailed analysis and actionable insights to support strategic and operational decisions, ensuring alignment with overall business objectives.
- Aggregate and interpret data from various sources to uncover trends and patterns, with a focus on process optimization and waste reduction.
- Collaborate closely with operations, supply chain, and product management teams across APAC to achieve organizational goals.
- Create and maintain dashboards that offer real-time visibility into key performance indicators (KPIs) across operations, logistics, purchasing, product, and management functions.
- Establish, measure, and refine KPIs to ensure they align with business objectives and drive continuous improvement.
Skills & Qualification
- Ability to present data insights clearly and persuasively to various stakeholders, including senior management and external partners.
- Ability to think critically and creatively to solve complex problems and optimize processes.
- Ability to analyze financial data and understand the financial impact of Lean initiatives on cost savings and ROI.
- Proficiency in visualization tools such as Tableau, Power BI, or QlikView for creating impactful dashboards and reports.
- Proficiency in Python and/or R for performing statistical analysis, creating predictive models, and managing large datasets.
- Experience with statistical methods such as regression analysis, hypothesis testing, and time-series analysis.
- Experience in planning, executing, and monitoring projects, including resource allocation and risk management.
- Strong focus on detail to ensure accuracy in data analysis and process improvements.
- Proven track record of successfully implementing practices in various operational settings.
- Proven ability to lead cross-functional teams and manage projects from initiation through completion.
- A bachelor’s degree in business management or a closely related field such as data science.
