Manager - Asset Management & Financial Data Analytics

About the role

ZMI is hiring a Manager - Asset Management & Financial Data Analytics. The role oversees asset performance, financial analytics, business intelligence, forecasting and strategic planning to optimise capital allocation and maximise shareholder value. It acts as a key business partner to senior leadership, turning financial and operational data into actionable insights, and covers drydocking programmes, vessel maintenance, ship management operations, plant maintenance expenditure and long-term asset lifecycle planning.

Key responsibilities

• Monitor and analyse the financial and operational performance of group assets and business units, and develop asset-level dashboards and KPIs for profitability, ROIC, cash generation and efficiency.
• Support investment evaluations, acquisitions, divestitures and capital allocation, and lead asset valuation and scenario analyses.
• Support annual budgeting, long-range planning and forecasting, analyse variances, build driver-based models and prepare executive presentations.
• Design and maintain analytics dashboards in Power BI, automate reporting, build predictive and prescriptive models and integrate financial, operational and market data.
• Support strategic initiatives with sensitivity analysis, scenario planning and risk assessment.
• Set data governance standards, work with IT, Finance, Commercial and Operations teams, and ensure compliance with corporate governance and financial policies.

Required profile

• 7-10 years of progressive experience in FP&A, corporate finance, asset management, business intelligence or financial analytics.
• Experience in holding companies, financial institutions, infrastructure, maritime, oil & gas, industrial or investment organisations is highly desirable.
• Proven experience developing executive dashboards and business intelligence solutions.

Required skills

• Advanced financial modelling, valuation, budgeting, forecasting and scenario/sensitivity analysis.
• Expert proficiency in Microsoft Excel and Power BI.
• SAP, Oracle, Microsoft Dynamics or other ERP experience.
• SQL, Power Query, Power Pivot and data warehouse concepts; exposure to AI-driven analytics is an advantage.