Job Summary:
The Financial Analyst will be responsible for analyzing financial data to support budgeting, forecasting, financial reporting, and business decision-making. The role involves developing financial reports, dashboards, analytical models, and management reports using Excel, SQL, Power BI, and AI-enabled analytics tools. The candidate will perform financial performance analysis, identify trends and anomalies, maintain data accuracy across enterprise systems, and leverage AI and automation technologies to improve reporting efficiency and operational processes. The role also requires collaboration with cross-functional teams to deliver data-driven insights and support financial planning and reporting activities.
Key Responsibilities:
• Analyze financial data to support budgeting, forecasting, reporting, and business decisions.
• Develop financial reports, dashboards, and analytical models using Excel, SQL, Power BI, and AI-enabled analytics tools.
• Perform variance analysis, trend analysis, forecasting, and financial performance analysis.
• Validate, reconcile, and maintain financial data across enterprise systems.
• Build and maintain financial models, KPIs, dashboards, and management reports.
• Utilize AI tools such as Microsoft Copilot, ChatGPT, Power BI Copilot, and similar platforms to accelerate data analysis, reporting, documentation, and business insights.
• Leverage AI capabilities to identify trends, anomalies, cost drivers, and opportunities for process improvement.
• Automate recurring financial reports, data analysis, and reporting processes using AI, Python, Power Automate, or other automation tools.
• Collaborate with Finance, Technology, Risk, Operations, and Business teams to deliver data-driven insights.
• Troubleshoot data and reporting issues and support month-end and quarter-end reporting activities.
• Prepare executive presentations, financial summaries, and recommendations using data and AI-assisted analysis.
• Participate in Agile/Scrum ceremonies and continuous improvement initiatives.
Required Qualifications:
• Bachelor's degree in Finance, Accounting, Economics, Business, Computer Science, Information Systems, Engineering, or a related field, or equivalent experience.
• Minimum of 5+ years of experience in Financial Analysis, Business Analysis, Data Analytics, or Financial Planning and Analysis (FP&A).
• Minimum of 4+ years of experience in financial reporting, budgeting, forecasting, variance analysis, and financial modeling.
• Minimum of 3+ years of hands-on experience with SQL for data analysis and reporting.
• Minimum of 4+ years of experience with Microsoft Excel, including advanced formulas, PivotTables, and financial modeling.
• Minimum of 2+ years of experience with Power BI or similar business intelligence tools.
• Minimum of 3+ years of experience working with large financial datasets and enterprise systems.
• Minimum of 2+ years of experience with Python, R, or other data analysis and automation tools.
• Minimum of 2+ years of experience using AI tools for data analysis, reporting, productivity, process automation, or business insights.
• Minimum of 2+ years of experience with financial systems such as ERP, General Ledger, Treasury, or Investment Management platforms.
• Minimum of 3+ years of experience working with cross-functional Finance, Technology, Operations, and Business teams.
• Minimum of 2+ years of experience with Agile/Scrum methodologies.
• Strong knowledge of financial concepts, KPIs, data quality, reconciliation, and management reporting.
• Strong analytical, communication, problem-solving, and stakeholder management skills.
Preferred Qualifications:
• Experience in Banking, Financial Services, Insurance, Wealth Management, or Investment Management.
• Experience with FP&A, Power BI, Tableau, Snowflake, or modern analytics platforms.
• Experience using Generative AI and AI-powered automation to improve financial reporting, forecasting, data analysis, and operational efficiency.
• Experience with Microsoft Copilot, ChatGPT Enterprise, Power BI Copilot, Power Automate, or similar enterprise AI solutions.
• Familiarity with responsible AI practices, data privacy, security, governance, and regulatory requirements.
