SECU

SECU

Financial Data Analyst II

Raleigh - Salisbury St · Mid

Sponsorship not specifiedDetected 3 hours ago
PythonSQLData AnalysisData VisualizationStatisticsFinancial ModelingAccountingForecastingBudgetingExcelHRISSASResearchPublic Speaking

About the role

  • If you are motivated and believe in the credit union philosophy of "People Helping People," join our team!
  • Disclaimer State Employees' Credit Union reserves the right to fill this role at a higher/lower level based on business need.

Responsibilities

  • Compile, organize, and analyze financial information in support of budgeting, forecasting, and decision-making processes.
  • Assist in developing and implementing process improvements and automated solutions.
  • Collaborate with cross-functional teams to gather data and insights for projects.
  • Support senior analysts in conducting financial research and special projects.
  • Capability to identify and document data quality issues, limitations and gaps that may exist.

Requirements

  • Bachelor's in Information Technology, Data Analytics, Accounting, Business, Finance or related Field
  • Required Knowledge, Abilities, Skills:
  • Required Knowledge, Abilities,
  • Prior experience developing and executing queries and/or reporting for data sets required.

Skills

  • Data Mining Techniques
  • Data Visualization
  • Programming for Data Analytics (e.g., Python or R)
  • Business Statistics
  • Database Management (e.g. SQL)
  • Financial Modeling Skills
  • Ability to analyze data, draw conclusions to make recommendations and communicate effectively with others in an understandable manner.
  • Demonstration of sound judgment in actions and decision-making.
  • Ability to organize work effectively and follow through on work activities and deliverables.
  • Capacity to multi-task and work effectively with exacting deadlines.
  • Ability to demonstrate flexibility and evolve with an ever-changing environment.
  • Attention to detail.

This listing is sourced directly from SECU's careers page and normalized into a canonical job model.