WHAT DOES A FINANCIAL DATA ANALYST DO?

Published: Mar 18, 2025 - The Financial Data Analyst performs daily, weekly, and monthly data extractions for Power BI reporting, updating supplemental data in Excel files. Enhances data accuracy by refreshing Power BI dataflows and datasets, and rigorously reviews results to ensure precision. Additionally, develops and modifies queries using Power Query, adjusts reports for period transitions, and thoroughly resolves issues, continuously seeking to improve data system efficiency and effectiveness.

A Review of Professional Skills and Functions for Financial Data Analyst

1. Financial Data Analyst Duties

  • Data Visualization: Prepare internal financial and commercial reporting & analytics through Tableau (including daily/weekly revenue reporting, P&L key performance indicators, monthly forecast analysis, etc.)
  • System Integration: Help convert reports to pull data from the new systems implemented
  • Financial Reporting: Assist with financial reporting and forecasting
  • Data Verification: Support in cross-checking month-end financial figures channel data
  • Financial Planning: Budget and forecast creation/analysis
  • Report Development: Build reports in Power BI, streamline the reporting process
  • Collaboration: Work closely with the data analytics department
  • Strategic Support: Supports other business strategies and initiatives
  • Variance Analysis: Perform detailed variance analysis to answer questions or resolve issues for service lines

2. Financial Data Analyst Details

  • Reporting Accuracy: Support weekly, monthly, and annual reporting requirements of the business unit, ensuring accuracy is maintained throughout.
  • Data Analysis: Use superior Excel and Power BI skills to analyze data from multiple systems and build insightful reports and models for senior leaders to identify areas of success and opportunities for improvement.
  • Business Analysis: Provide key business analysis and support ad-hoc reporting requests.
  • Financial Planning: Support budget planning and financial forecasting processes.
  • Data Governance: Maintain data governance to ensure consistency and accuracy in reporting as well as to identify and solve any discrepancies that arise promptly.
  • Relationship Building: Build strong working relationships with key stakeholders to understand the business and the business needs.
  • Proactive Initiative: Demonstrate initiative by consistently searching for areas of improvement and bringing forward new ideas and solutions.
  • Data Management: Manage and further develop the data models used for reporting, including financial and product/client data, ensuring that they remain complete, up-to-date, and free from error.
  • Hierarchy Maintenance: Maintain and update the relevant hierarchies (clients, currencies, accounts, etc) used for MI reporting, based on input from the commercial and finance teams.
  • Data Structure Analysis: Understand the structure and flow of data, to make improvements or fix issues.

3. Financial Data Analyst Responsibilities

  • Data Retrieval: Run queries and reports out of systems to get data for Power BI (daily, weekly, monthly).
  • Data Updating: Manually update supplemental data (Excel files).
  • Data Refreshing: Refresh Power BI dataflows & datasets and review results for accuracy.
  • Query Development: Modify existing queries and create new ones (Power Query).
  • Report Adjustment: Adjust reports as needed when moving from one period to the next.
  • Issue Resolution: Thoroughly investigate issues and own them until resolved.
  • Process Improvement: Identify opportunities for improvements in efficiency, accuracy, and effectiveness.
  • Documentation Maintenance: Maintain existing documentation and create new documentation.
  • System Enhancement: Contribute toward improving the related systems and processes that create data.
  • Financial Analysis Support: Provide occasional support with more traditional financial analyst tasks.

4. Financial Data Analyst Accountabilities

  • Stakeholder Engagement: Engage with project stakeholders and support the identification of areas where analytics can drive business value, frame business problems into analytic questions, and influence strategic decision-making by supporting the presentation of sophisticated data analytics in a simple, clear, and meaningful way.
  • Cross-functional Collaboration: Collaborate closely with cross-functional teams across OptumCare National and local clinics as well as other OptumHealth businesses to stay informed on key initiatives, elicit business domain expertise, learn the drivers of each business area, gather and consolidate data, and build valuable analytics.
  • Strategic Participation: Participate in discussions with leadership to help identify areas of opportunity that can be validated using data, business knowledge, and local partnerships.
  • Analytic Development: Support analytic development by leveraging varied techniques using many data sources, advanced forecasting models, financial and operational metrics, and other key performance indicators.
  • Data Visualization: Create visualizations using multiple data sources that convey complex insights in a way that’s easily interpreted and consumed by leadership.
  • Ad-hoc Support: Provide ad-hoc support to OH Analytics leadership on a variety of key initiatives that span numerous projects and initiatives.
  • Financial Reporting: Build and manage financial reporting and insight processes.
  • Expertise in Anaplan: Be a subject matter expert for all things including Anaplan.
  • Interdepartmental Liaison: Liaise with senior members of staff across departments in the business.
  • Presentation Skills: Present the results of any analysis carried out in digestible formats.

5. Financial Data Analyst Functions

  • Data Analysis: Timely and accurate analysis of daily data, covering both financial and marketing metrics.
  • Trend Analysis: Detailed trend and seasonality analysis.
  • Project Assistance: Assisting in divisional and channel projects.
  • Stakeholder Reporting: Daily reporting to key senior stakeholders across the group.
  • Business Partnering: Business partnering with the Marketing Finance team.
  • Team Collaboration: Work closely with various teams, including management, developers, and database designers, and external data partners to provide the 'best-in-breed' data offering to clients and end users.
  • Data Evaluation: Evaluate data, and make decisions and recommendations to improve the quality of the Ownership, Securities, and Corporate Governance data.
  • Functionality Design: Design and implement new functionalities to further enhance the usability of the data.
  • Data Control: Apply data control measures to provide the highest possible data quality to clients.
  • Data Support: Collaborate with internal stakeholders and provide data support measures to address client inquiries.
Relevant Information
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