Data Scientist For Pooling

Position Title: Data Scientist

Location: UnionBank Plaza, Ortigas, Pasig City

About The Role

The Data Scientist is responsible for transforming enterprise data into actionable insights, predictive models, and intelligent solutions that drive business growth, operational efficiency, risk management, and customer experience improvements across the bank. The role leverages advanced analytics, machine learning, artificial intelligence (AI), and statistical modeling techniques to solve complex business challenges and support strategic decision-making.

Working closely with Data Engineers, Data Product Managers, Business Units, Technology Teams, Risk, Operations, and Senior Management, the Data Scientist develops data-driven solutions that enhance the bank's digital transformation, data modernization, customer engagement, fraud detection, and financial performance initiatives. This role serves as a key contributor to building a data-driven culture and advancing the bank's analytics and AI capabilities.

What You'll Do

• Develop predictive, prescriptive, and descriptive analytics models that support business growth, operational excellence, customer experience, and risk management objectives.
• Analyze large, complex, and diverse datasets from core banking systems, digital channels, payments platforms, CRM systems, data warehouses, and external sources.
• Design, build, validate, deploy, and monitor machine learning and artificial intelligence models for business use cases.
• Collaborate with business stakeholders to identify opportunities where data science can generate measurable business value.
• Perform data exploration, feature engineering, statistical analysis, and hypothesis testing to uncover trends, patterns, and business insights.
• Develop customer segmentation, propensity, recommendation, churn prediction, and customer lifetime value models to support customer acquisition and retention strategies.
• Build fraud detection, anomaly detection, risk scoring, and behavioral analytics models to strengthen operational and risk management capabilities.
• Create forecasting models for business planning, product performance monitoring, customer behavior prediction, and operational optimization.
• Work closely with Data Engineers to ensure reliable and scalable access to high-quality data required for analytics and machine learning solutions.
• Support the deployment and operationalization of models through MLOps, automation frameworks, APIs, and cloud-based analytics platforms.
• Develop dashboards, reports, visualizations, and presentations to communicate analytical findings and recommendations to technical and non-technical stakeholders.
• Establish model governance practices, including model validation, performance monitoring, explainability, documentation, and periodic recalibration.
• Ensure analytics and AI solutions comply with data governance, cybersecurity, ethical AI principles, Data Privacy Act requirements, BSP regulations, and internal policies.
• Participate in enterprise data strategy initiatives, innovation projects, proof-of-concept activities, and technology transformation programs.
• Conduct research on emerging trends in artificial intelligence, machine learning, generative AI, advanced analytics, and financial technologies.
• Serve as a subject matter expert on analytics, machine learning, and AI, contributing to knowledge-sharing and capability-building initiatives across the organization.
• Participate in incident investigations, root cause analyses, and problem-solving activities involving data models or analytics solutions.
• Continuously improve analytics methodologies, model performance, and data science practices within the organization.
• Perform other duties as may be assigned.
  
  

• Bachelor's Degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Technology, Economics, Actuarial Science, or a related field. A Master's Degree is an advantage.
• At least 3-5 years of experience in Data Science, Advanced Analytics, Machine Learning, Artificial Intelligence, Quantitative Analysis, or related fields, preferably within banking, financial services, fintech, or highly regulated industries.
• Strong expertise in statistical analysis, predictive modeling, machine learning algorithms, and data mining techniques.
• Proficiency in Python, R, SQL, and analytics libraries/frameworks such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or equivalent.
• Experience working with large-scale datasets, data warehouses, cloud analytics platforms, and modern data ecosystems.
• Strong business acumen, communication, stakeholder management, and problem-solving skills with the ability to translate business challenges into analytics solutions.