Data Analyst – Dialog Axiata PLC

Job Purpose:

Responsible for importing, processing, analyzing, modeling, and presenting data for future opportunities and improvements. Deliver analytics, dashboards, or reports for strategic decision-making purposes and manage operational data requests from relevant Business Units. Systematically gather and appraise relevant data, including numerical, verbal, and other sources of information. Mine data from primary and secondary sources, then reorganize them in a format that can be easily read by either human or machine.

The Job:

• Synthesize research findings in easy-to-understand terms for the business.
• Apply simple problem-solving methodologies to diagnose and solve operational and interpersonal problems.
• Recommend resource requirements and collaborate with relevant stakeholders.
• Provide business metrics for the overall project to show improvements.
• Implement enhancements and fixes to systems as needed.
• Provide ongoing tracking and monitoring of performance of decision systems and statistical models.
• Communicate and work with business subject matter experts.
• Lead initiatives for continual improvements.
• Design experiments as required to try out use cases.
• Define performance tracking metrics including (but not limited to) incremental takeup, revenue, etc.
• Retrain/periodic revision of model performance.
• Measure impact/ROI and identify further optimization.
• Provide guidance to achieve consistent commercial growth and execution excellence in the division/BU.
• Execute campaigns with functional units and measure the effectiveness of campaigns.
• Influence stakeholders for driving new projects and campaigns.
• Conduct in-house consultative meetings with internal stakeholders for insights sharing and get feedback to improve special campaigns.
• Conduct continuous assessments of adoption programs and set clear objectives and report performances.
• Manage operational report requests via Tableau/Safe Harbor.
• Attend development of Analytics at the EDGE project.
• Work with business/support units to identify opportunities for leveraging organization’s data to drive business.
• Collect data from internal & external sources.
• Clean and prepare data as suitable for analytical tasks.
• Carry out exploratory data analysis, visualization, hypothesis testing.
• Present findings & actionable intelligence to stakeholders & senior management through data visualization tools.
• Define activities, strategic direction, scope, and timelines on data science projects.
• Develop dashboards to cater to divisional business requirements.
• Work in cross-functional teams (internal & external) to develop & trial use cases.
• Carry out data preparation, cleansing, exploratory analysis, feature engineering at scale.
• Maintain documentation of methodology, source codes, version control & other best practices in development operations.
• Adhere to agile development practices.
• Write reports and deliver presentations to all levels of colleagues and peer groups in ways that support the business.
• Conduct both quantitative and qualitative analysis.
• Research on industry best practices and work with internal/external parties on RnD tasks.
• Prepare roadmaps, investment papers, and research on emerging technologies.
• Communicate and work with business subject matter experts for continuous improvement of methodologies.
• Carry out trials, adaptations of methodologies.
• Knowledge sharing and collaboration building.
• Acquire certifications offered through MOOC.
• Ensure Predictive models are live and automated within the key business processes.
• Training & Certification on SQL, Python OR R & other necessary tools to become a subject matter expert.
• Groom Edge Users on SQL/Tableau & empower on self-extractions.
• Data Quality Management & Data Cleansing for the Data relevant for the Division.

The Person:

• BSc in IT/Computer Science/AI/Data Science/Statistics, Software Engineering, Economics, and Business.
• Should score 70% above from entry-level exam.
• Passionate about creating value through scientific methods and data analysis.
• Axiata Fast-forward Training.
• Tolerance for ambiguity and openness to feedback from design, strategy, and other disciplines.