Data Modelling Manager Data Science

Reporting to: Data Science & Analytics Group Manager

Duty Post: BGC Taguig

Application Duration: This job posting will remain open until the vacancy is filled.

Data Modelling Manager (Data Science)

The Data Science Data Modelling Manager is a business-facing role responsible for transforming raw data into structured analytical models that support consumer insights, reporting, and data-driven decision-making. The role ensures data from multiple environments, such as the Data Lake and Data Warehouse, is harmonized and modeled to meet business analytics and commercial needs.

The position does not manage raw data or infrastructure. Instead, it partners closely with IT, Data Governance, and technical teams to ensure analytical outputs are built on validated and approved data sources. The role translates business requirements into scalable data models and frameworks that enable actionable insights and informed decision-making.

Position Description

1. Analytical Data Modelling

Develops and maintains structured data models that enable dashboards, reporting, and insights. Aligns models with business definitions and evolving analytical requirements.

2. Data Integration and Preparation

Collaborates with IT and Data Governance to ensure all analytical datasets originate from validated sources within approved environments (Data Lake, Data Warehouse). Defines transformation rules and logic to prepare data for business use.

3. Insight Generation and Reporting

Analyzes data to identify trends, performance drivers, and improvement opportunities. Delivers actionable recommendations that support strategic and operational decision-making.

4. Governance and Documentation

Ensures all modeling activities comply with data governance standards. Maintains clear documentation to support transparency, consistency, and continuity.

5. Stakeholder Collaboration

Engages commercial teams to understand data and insight requirements. Provides structured solutions and communicates findings effectively to enable informed decisions.

Position Requirements:

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• At least 5 years of experience in data analytics, data modelling, or related business-focused analytical roles.
• Demonstrated experience transforming raw data into structured analytical datasets for reporting and insights.
• Strong understanding of data integration, data definitions, and data governance principles from a business perspective.
• Experience partnering with IT to align on data requirements and ensure use of validated data sources.
• Experience in marketing, sales analytics, or commercial performance management is an advantage.
• Fluent in both written and verbal English (strong communication and collaboration skills)

Functional Skills:

• Business-Focused Data Modelling-Designs and maintains analytical data structures that convert raw data from approved environments (Data Lake, Data Warehouse) into business-ready formats. Ensures alignment with business definitions while coordinating with IT for implementation.
• Data Transformation for Analytics-Prepares and harmonizes data from validated sources within approved environments (e.g., Data Lake, Databricks, DWH) to create clean, analysis-ready datasets. Focuses solely on transformation and analytical preparation, not data ownership.
• Technical Proficiency for Insight Generation-Leverages SQL and Python for data preparation, validation, and transformation. Utilizes analytics tools such as Power BI, Synapse, or Databricks to support business reporting. Familiar with cloud environments (e.g., Azure) for analytical enablement.
• Analytics and Insight Development-Applies analytical and statistical techniques to generate insights that support commercial planning, targeting, and performance monitoring.
• Data Governance Alignment- Ensures all analytical activities comply with established data governance standards. Collaborates with Data Governance and IT to verify the use of validated and approved data sources.
• Visualization and Communication-Delivers insights through clear dashboards, reports, and visual summaries tailored to business users and senior management.
• Project & Stakeholder Management-Leads analytics-related initiatives, collaborates with cross-functional stakeholders, and coordinates with IT and vendors to deliver timely and accurate analytical outputs.