Network Data Scientist

Globe Telecom, Inc.; Taguig; On-site; PHP 558,000 - 892,800; Full time

Job summary

Globe Telecom, Inc. is seeking a professional to design, develop, and deploy statistical models and machine learning solutions to enhance network performance. This role involves collaborating with various teams to provide analytical support and lead advanced analytics initiatives.

The ideal candidate should have strong skills in statistical analysis and machine learning, along with an ability to communicate complex insights effectively. This is an equal opportunity position in the dynamic telecommunications industry.

Qualifications

• Experience in statistical modeling and advanced analytics.
• Knowledge of machine learning and AI techniques.
• Ability to communicate complex analytical results effectively.

Responsibilities

• Provides analytical support to Network Perception and Insights.
• Leads data mining efforts across diverse network datasets.
• Develops predictive models for network planning and optimization.
• Applies statistical methods to network performance data.
• Communicates analytical results to stakeholders.

Skills

Statistical analysis

Machine learning

Data mining

AI techniques

Cross-functional collaboration

Job description

Overview

Designs, develops, and deploys statistical models, machine learning solutions, and advanced analytics to deliver descriptive, diagnostic, predictive, and prescriptive insights aligned with organizational and network strategy objectives. Translates complex network and subscriber data into actionable, data‑driven recommendations that improve network performance, guide investment decisions, and enhance customer experience.

Responsibilities

• Provides analytical and data science support to the Network Perception and Insights section and the Network Analytics section, enabling deeper understanding of network performance, subscriber experience, and competitive positioning through advanced analytics and AI/ML‑driven insights.
• Leads data discovery and data mining efforts across diverse network datasets, uncovering hidden patterns, anomalies, and relationships from large‑scale internal and external data sources.
• Develops and oversees predictive and prescriptive models to support network planning, optimization, and performance management (e.g., capacity forecasting, site prioritization, experience‑driven optimization, and site availability prediction).
• Applies statistical analysis, machine learning, and AI techniques to network performance (KQI/KPI), subscriber experience (CEI, NPS), site availability, and business outcome data.
• Conducts root‑cause analysis, post‑mortem modeling, and correlation/causal studies across network events, programs, incidents, and site downtime drivers (e.g., customer perception regression analysis – NPS drivers).
• Supports business and operational domains by delivering advanced analytics use cases, including network‑marketing claim validation, network‑experience‑to‑revenue modeling, network‑business performance correlation, and site availability optimization.
• Leverages third‑party and competitive datasets (e.g., Ookla, FB Meta, VOC surveys) to enrich internal analyses and improve model robustness.
• Leads data discovery and exploratory analysis, identifying trends, anomalies, and high‑value patterns across multi‑source network and operational data.
• Collaborates with cross‑functional teams (Network Perception Insights / Network Analytics in NAI and other divisions such as Network Access, Core, Transport, Planning & Engineering, and Operations) to apply insights to site planning, upgrades, capacity optimization, and site uptime improvement.
• Communicates complex analytical results clearly to technical and non‑technical stakeholders, enabling informed decision‑making at operational and leadership levels.
• Ensures analytics outputs are actionable, aligning models and insights to strategic objectives, operational needs, site availability, and subscriber‑centric network improvements.

Equal Opportunity Employer. Globe’s hiring process promotes equal opportunity to applicants. Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as in posting vacancies, selecting, and interviewing applicants.