Financial Data Analyst

Qualifications and Experience

• Bachelor's degree in a relevant field, such as finance, statistics, mathematics, or computer science.
• 3+ years of experience as a data analyst, preferably in a business environment.
• Strong analytical and problem‑solving skills with a keen attention to detail.
• Proficient in data analysis tools such as SQL, Python, R, or SAS.
• Proficient in scripting in SQL and basic understanding of reporting tools.
• Experience with data visualization tools such as Tableau, Power BI, or Qlik View.
• Experience with spreadsheet software like Excel or Google Sheets.
• Excellent written and verbal communication skills with the ability to present complex data analysis results to both technical and non‑technical stakeholders.
• Familiarity with geospatial data.
• Willingness to learn new application and data structures.
• Familiarity with Gen Tax application.
• Background in analytics in a tax environment.
• Proficiency in building reports with SSRS or SAP Crystal Reports.
• Previous work in tax administration and development of new taxing programs.
• Experience in administration of taxes including sales tax, short‑term rental tax, alcohol beverage licensing, and occupational licensing.

Construct bridged reports between two record systems. Gather, examine, and decode extensive datasets through statistical methods and tools. Generate reports, dashboards, and visualizations to convey data insights to stakeholders. Develop and sustain databases, data warehouses, and data systems to secure data precision and integrity. Detecting trends and patterns in intricate data sets is vital for formulating data‑driven suggestions that improve business efficacy.

Pair and blend data sets using specific variables including addresses with known variation between sources.

Collaboration with cross‑functional teams is essential to deliver insights and recommendations that inform business decisions. It's important to effectively communicate complex data analysis findings to stakeholders, regardless of their technical background. Keeping abreast of the latest trends and technologies in data analysis is crucial for enhancing our analytical methods.

Works independently to satisfy prioritized tasks and duties.

Self‑starter that can learn and operate unfamiliar applications and tools as needed to perform duties.