Data Science Manager, Southeast Asia

Data Science Manager, Southeast Asia

Title:

Data Science Manager, Southeast Asia Reports to:

Regional Head of Southeast Asia Classification:

Full-time Start Date:

Immediate Position Summary

Women’s World Banking is seeking a Data Science Manager to lead the development of data-driven insights, credit risk models, and AI-powered tools that advance financial inclusion and climate resilience across Southeast Asia. Based in Jakarta, this role will strengthen WWB’s data analytics capabilities to drive evidence-based product innovation, responsible digital lending, and systemic market change. The Data Science Manager will work closely with Advisory, Research, and Policy teams to translate raw data into actionable insights that enable financial service providers (FSPs), regulators, and policymakers to better serve women-led MSMEs and underbanked communities. This position goes beyond model-building—it’s about creating data ecosystems that unlock opportunity. The ideal candidate is both a technical expert and a systems thinker, passionate about using data, AI, and machine learning to improve financial access, optimize risk management, and enable sustainable growth for low-income women and micro-entrepreneurs. Roles and Responsibilities

Data Science & Model Development

Lead the design, development, and deployment of credit scoring, behavioral scoring, and risk segmentation models tailored to women-led MSMEs and informal entrepreneurs. Develop AI/ML algorithms and analytical frameworks that integrate alternative and non-traditional data (e.g., G2P, QRIS transactions, mobile usage, environmental factors). Build tools and models that advance climate-smart credit decisioning, integrating resilience and sustainability indicators into risk assessments. Conduct model validation, back-testing, and performance monitoring to ensure accuracy, fairness, and regulatory compliance. Data Analytics & Insight Generation

Develop and maintain data visualization dashboards, performance tracking tools, and automation pipelines to monitor impact and business outcomes. Generate insights from internal and external datasets to inform product design, policy recommendations, and strategic decisions. Collaborate with Research and Policy teams to ensure data findings are translated into actionable ecosystem-wide advocacy and learning. Partner with FSPs, regulators, data providers, and fintechs to build data-sharing frameworks and open-data collaborations that enable inclusive innovation. Contribute to the design of ethical and responsible AI frameworks, ensuring transparency, fairness, and gender equity in data use. Identify data and analytics barriers across the market, channel insights to WWB’s Policy team, and co-develop strategies to strengthen the regional data ecosystem. Team Leadership & Capacity Building

Lead a small team of external consultants to execute high-quality analytical projects. Mentor internal teams and partner organizations in data analytics literacy, responsible AI practices, and evidence-based decision-making. Promote a culture of learning, curiosity, and collaboration within WWB’s Southeast Asia team. Required Qualifications

Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Econometrics, or a related quantitative field. 8–10+ years of relevant experience in data science, credit analytics, or financial risk modeling, ideally within banking, fintech, or development finance. Strong proficiency in Python, R, SQL, and machine learning libraries (scikit-learn, TensorFlow, XGBoost, etc.). Experience developing credit risk, behavioral, or customer segmentation models and applying them to business or inclusion contexts. Strong background in data visualization tools (Power BI, Tableau, Looker) and cloud environments (AWS, GCP, Azure). Proven ability to manage multiple projects and collaborate effectively with cross-functional teams. Excellent communication skills with fluency in English and Bahasa Indonesia. Preferred Qualifications

Experience working with financial inclusion, MSME, or development finance data ecosystems. Deep understanding of AI for inclusion, climate data integration, and responsible machine learning principles. Track record of identifying data or regulatory barriers and contributing to broader data policy advocacy or open-data initiatives. Demonstrated experience leading external consultants and data vendor partnerships. Strong stakeholder management skills, able to translate complex analytics into insights for FSP executives, funders, and policymakers. Measure of Success

Within the first 75 days: Lead a diagnostic of WWB’s current data assets, analytics needs, and model opportunities. Develop a roadmap for data ecosystem strengthening, aligned with WWB’s Southeast Asia strategy and Gates/DFAT-funded projects. Prototype at least one AI-enabled scoring or segmentation model for women-led MSMEs. Collaborate with the Policy and Advisory teams to identify market-level data gaps and propose actionable pathways for systemic change. Embody Women’s World Banking’s values: Think Big, Own & Commit to It, Smarter Together. Seniority level

Mid-Senior level Employment type

Full-time Job function

Research Industries

Financial Services and Non-profit Organizations

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