Job Requirements

• Candidate must possess at least a Diploma, Advanced/Higher/Graduate Diploma, bachelor’s degree, Post Graduate Diploma, Professional Degree, master’s degree in any fields.
• Preferable with 2 years of working experience in the related field is required for this position.
• Experience in extracting, transforming and porting data from source systems to data analytics platform(s) and reports using Tableau, Dynamics 365, etc.
• Experience in analyzing different types of data to support business needs and present the results in concise visualization formats using Power BI, Looker Studio, and other dashboarding tools.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.
• Experience working with and creating data architectures.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Experience in using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
• Has an inquisitive mind and proactivity to challenge the norms constructively.
• Must have initiative, drive and work independently with minimum supervision and a good team player
• Excellent verbal and written communication skills in English and the language of supporting market (at least C1).

Responsibilities

• Extract, transform, and analyse data from multiple sources to provide actionable insights that support operational and strategic decision-making.
• Design, build, and maintain interactive dashboards, scorecards, and visualisations to track business performance against key KPIs and SLAs.
• Partner with cross-functional teams (e.g., Operations, WFM, QA, L&D, and Sales Enablement) to understand requirements and translate them into effective data solutions.
• Conduct deep-dive analysis on performance trends, identifying gaps, opportunities, and root causes, and provide clear recommendations to drive business improvements.
• Support forecasting, capacity planning, and performance modelling to enable proactive business planning.
• Automate recurring reporting processes to improve efficiency, accuracy, and timeliness of data delivery.
• Ensure data integrity, security, and compliance in all reporting and analytics processes.
• Provide ad-hoc analysis and insights to support new initiatives, business reviews, and senior leadership discussions.
• Drive innovation in reporting methodologies and proactively identify opportunities to enhance data storytelling and stakeholder engagement.
• Collaborate closely with management to contribute to the continuous improvement of operational excellence.