Total 2 senior manager job vacancies in The Philippines

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Leads a diverse team processing global payments, auditing travel & expense claims, invoice processing, accurately and timely.
• Reviews and approves payment proposals and ensure compliance with accounts payable policies, audit requirements and controls.
• Reviews and approves Travel & Expense exceptions and ensure compliance with Travel & Expense policies, audit requirements and controls.
• Analyzes KPI’s and performance scorecards to improve efficiency and the level of customer service.
• Develops reports and continuous improvements that will benefit Accounts Payable and Travel & Expense.
• Provides record of assets, liabilities and other financial transactions.
• May interpret reports and records for managers/stakeholders.
• Provides problem and invoice resolution assistance to vendors and internal company personnel with tact and diplomacy; act as a liaison between departments and vendors
• Be proactive and identify areas in need of improvement and take action to implement process improvements when appropriate to increase overall department capacity
• Provides effective and timely follow through with internal and external inquiries, issues and concerns
• Reviews workload and adjusts resources to provide accurate and timely processing consistent with policy and controls

Develops and implements scalable data pipelines, transforms complex datasets into actionable insights, and creates data-driven solutions to support strategic decision-making and business growth.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Design, build, and maintain robust data pipelines for collecting, processing, and integrating data from various sources.
• Ensure that data is accurately and efficiently transferred and transformed between systems.
• Create dashboards, reports, and visualizations to support decision-making.
• Collaborate with cross-functional teams to understand their data needs and provide actionable, data-driven recommendations.
• Use statistical, machine learning, or deep learning techniques to analyze and model data, identify trends, patterns, and relationships, and provide applicable solutions.
• Develop predictive models using machine learning algorithms to forecast trends and future outcomes. Then, deploy these models and systems, and monitor and maintain them to ensure they are working effectively.
• Document data workflows, processes, and technical specifications.
• Stay updated with industry trends and best practices to continuously improve data engineering practices.