DATA SCIENTIST

Bank of the Philippine Islands (BPI); Makati; Presencial; PHP 900.000 - 1.900.000; Tempo integral

Resumo da vaga

Bank of the Philippine Islands (BPI) seeks a Data Scientist to develop and validate predictive models and scorecards across Mass Retail. You will transform data into insights, support growth, risk management, and decision-making, while collaborating with cross-functional teams.

The role emphasizes model deployment, governance, and ongoing performance monitoring, with leadership potential and strong communication skills expected.

Qualificações

• Bachelor's degree in a quantitative field; master's preferred.
• 3+ years in data science, risk modeling, or related consumer lending.
• Strong knowledge of data modeling, analytics, and insights.
• Experience with credit, risk, fraud analytics is a plus.
• Proficient in Python, SAS, VBA, Tableau; Excel/PowerPoint skills required.

Responsabilidades

• Develop credit scorecards and predictive models for growth and risk.
• Analyze large datasets using EDA to ensure data quality.
• Design and validate ML models using internal/external data.
• Assess methodologies and document model development.
• Monitor performance and propose enhancements or retirement.
• Lead deployment with testing, validation, and user acceptance.
• Collaborate with risk, operations, technology and business units.
• Present findings and recommendations to stakeholders.
• Provide guidance to Data Analysts and support analytics programs.

Conhecimentos

Data analytics

Communication

Stakeholder management

Project management

Critical thinking

Formação

Bachelor's degree in Statistics, Mathematics, Economics, Data Science, Engineering, or related field

Master's degree preferred

Ferramentas

Python

SAS

VBA

Tableau

Excel

PowerPoint

Descrição da vaga

The Data Scientist develops, validates, implements, monitors, andenhances predictive models and scorecards that support business growth, riskmanagement, and decision-making across the Mass Retail Segment. The roletransforms complex data into actionable insights and analytics-driven solutionsto optimize portfolio performance, customer acquisition, collections, andprofitability.

Main Accountabilities

• Develops credit application, behavior, revenue, propensity, collections,fraud, and recovery scorecards and predictive models to support business andrisk objectives
• Assesses, prepares, and analyzes large datasets using exploratory dataanalysis techniques to ensure data quality and modeling readiness
• Designs, builds, and enhances statistical, machine learning, andpredictive analytics models using internal and external data sources
• Performs qualitative and quantitative assessments of modelmethodologies, design, assumptions, and implementation processes
• Maintains comprehensive model documentation, including developmentmethodologies, key assumptions, and model changes
• Monitors model performance and portfolio outcomes to identify risks,validate effectiveness, and recommend model enhancements or retirement
• Establishes performance benchmarks and monitoring frameworks to ensurecontinued model relevance and predictive power
• Leads the deployment of models through rigorous testing, validation, anduser acceptance procedures to ensure implementation accuracy
• Coordinates with business units, operations, technology teams, and riskmanagement stakeholders to support model implementation and governancerequirements
• Secures required approvals and ensures compliance with the bank’s modelrisk management framework and regulatory standards
• Presents analytical findings, model results, and strategicrecommendations to stakeholders and management to drive understanding andadoption
• Collaborates with enterprise data scientists and cross-functional teamson bank-wide analytics, modeling, and data science initiatives
• Provides guidance and oversight to Data Analysts in support of analyticsand modeling activities

Qualifications

• Bachelor's degree in Statistics, Mathematics, Economics, Data Science,Engineering, or a related quantitative field
• Master's degree in Statistics, Mathematics, Economics, Data Science,Engineering, or a related discipline preferred
• At least 3 years of experience in Data Science, Risk Modeling, CreditRisk Management, Collections, Fraud Analytics, or related consumer lendingdisciplines
• Strong knowledge of data modeling, data management, data analytics, andinsight generation
• Strong understanding of risk modeling, predictive analytics, machinelearning, and statistical methodologies
• Proficient in Python, SAS, VBA, Tableau, and other data analytics tools
• Proficient in Microsoft Excel, PowerPoint, and related productivityapplications
• Experience working with credit, collections, fraud, or risk managementsystems
• Strong analytical, critical thinking, and problem-solving skills
• Excellent written and verbal communication skills with the ability topresent complex data in a clear and actionable manner
• Strong stakeholder management, negotiation, and relationship-buildingskills
• Strong project management and execution capabilities
• Demonstrated leadership and people management skills
• Ability to independently define business problems, perform comprehensiveanalyses, and formulate data-driven recommendations
• Ability to thrive in a fast-paced environment while managing multiplepriorities and meeting deadlines without compromising quality