Top Machine Learning Jobs in Manila

The Analytics Modeling Lead is responsible for developing credit risk management and business intelligence solutions, engaging with clients, leading analytic teams, and using advanced machine learning techniques to deliver predictive insights for the financial services sector. Responsibilities include designing data programs, creating analytical presentations, and mentoring junior staff.

The AI Project Manager will oversee the planning, execution, and delivery of AI/ML projects, collaborating with stakeholders and cross-functional teams to ensure successful outcomes. Responsibilities include project planning, risk management, quality assurance, and continuous improvement, while fostering strong relationships with stakeholders to communicate project status and business value.

The Customer Insights Specialist at S&P Global Market Intelligence will analyze customer feedback using Qualtrics, design surveys, collaborate with cross-functional teams, and present insights to enhance customer experience and inform business strategies. Responsibilities include project management from implementation to delivery of insights and maintaining dashboards for stakeholder communication.

The Forecasting Strategy and Innovations Lead will monitor forecast model performance, develop new models or improve existing ones, and act as the Technical Point of Contact for the Business Forecasting team. The role involves research and development of machine learning solutions to address business requirements, alongside engaging with business partners to translate needs into technical specifications.

As a Data Strategist, you will analyze business problems and propose data-driven solutions, delivering actionable insights in collaboration with machine learning researchers and engineers.

As a Data Strategist at GCash, you will analyze business problems and frame them into actionable data solutions. Collaborating with machine learning researchers and engineers, your role involves delivering machine learning models and visual insights to inform business strategy.

Design and develop scalable machine learning systems, conduct data analysis, improve existing models and workflows, collaborate with stakeholders, and document best practices.

The Supervisor, Engineering AI is responsible for implementing AI use cases, designing and developing workflows, and improving business processes through innovative AI solutions. They will work with various teams to enhance efficiency, evaluate existing systems, and facilitate training on AI technologies, while staying updated on advancements in the field.