Finance & Investment Data Analyst

Key Responsibilities

• Analyze and model large datasets related to manufacturing costs, raw material prices, production performance, utility consumption, and financial performance.
• Identify trends, risks, and opportunities to support data-driven business decisions.
• Develop and maintain interactive dashboards and reports using Power BI, Tableau, or similar analytical tools.
• Monitor key financial and operational metrics, including profitability, cost variances, productivity, and investment performance.
• Track and analyze commodity market trends, particularly copper, aluminum, polymers, and other strategic raw materials.
• Support procurement and business teams through forecasting models and pricing analysis to optimize purchasing decisions.
• Monitor Capital Expenditure (CAPEX) and Operating Expenditure (OPEX) performance across production facilities.
• Identify financial leakages, cost optimization opportunities, and areas for operational improvement.
• Support investment evaluations through financial analysis, business case development, and profitability assessments.
• Develop insights into product margins, asset utilization, and return on investment.
• Build predictive models to support budgeting, forecasting, demand planning, and market trend analysis.
• Leverage advanced analytics to improve financial planning and strategic decision-making.

Qualifications

• Bachelor's degree in Finance, Economics, Data Science, Statistics, Business Analytics, Industrial Engineering, or a related quantitative discipline.
• 2–5 years of experience in data analytics, financial analysis, business intelligence, investment analysis, or controlling within a manufacturing or industrial environment.
• Strong proficiency in Advanced Excel, Power BI, SQL, and data visualization tools.
• Experience with financial modeling, cost analysis, budgeting, forecasting, and profitability analysis.
• Knowledge of commodity markets, manufacturing cost structures, and investment evaluation methodologies is highly preferred.
• Experience with Python or R for data analytics and predictive modeling is a strong advantage.
• Strong analytical thinking, problem-solving, and stakeholder management skills.