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Financial & Data Analyst
Financial & Data AnalystPavago • Mesa, AZ, US
Financial & Data Analyst

Financial & Data Analyst

Pavago • Mesa, AZ, US
[job_card.30_days_ago]
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  • [job_card.full_time]
[job_card.job_description]

Financial Analyst / Data Analyst

Position Type : Full-Time, Remote

Working Hours : U.S. client business hours (with flexibility for reporting deadlines and project cycles)

About the Role :

Our client is seeking a Financial Analyst / Data Analyst to build models, analyze performance data, and deliver insights that guide strategy and decision-making. This role requires strong analytical skills, financial acumen, and proficiency with modern data tools. The Analyst serves as a bridge between raw numbers and executive decisions, ensuring reporting is accurate, timely, and actionable.

Responsibilities : Financial Modeling :

  • Build and maintain 3-statement models (P&L, balance sheet, cash flow).
  • Create scenario and sensitivity analyses to evaluate risks and opportunities.
  • Model ROI, IRR, break-even, and valuation scenarios for projects or investments.

Data Analysis :

  • Query SQL databases and work with large datasets.
  • Clean and transform data using Python, R, or Excel advanced functions.
  • Conduct variance analyses to compare actuals vs. budgets / forecasts.

    • Reporting & Dashboards :

  • Prepare monthly management reporting packages and board decks.
  • Build KPI dashboards using Tableau, Power BI, or Looker.
  • Ensure consistent reporting definitions across finance and operations.

    • Forecasting & Budget Support :

  • Collaborate with FP&A teams to refine budgets and forecasts.
  • Incorporate real-time business performance into rolling forecasts.

    • Data Quality & Governance :

  • Validate data sources for accuracy and consistency.
  • Document methodologies for transparency and repeatability.

    • Collaboration :

  • Partner with finance, sales, operations, and leadership to align metrics with goals.
  • Translate data into clear, actionable insights for non-technical stakeholders.

    • What Makes You a Perfect Fit :

  • Analytical thinker who can turn complex data into simple insights.
  • Detail-oriented, with high standards for accuracy.
  • Strong communicator equally comfortable with spreadsheets and executive presentations.
  • Proactive in identifying trends, risks, and improvement opportunities.

    • Required Experience & Skills (Minimum) :

  • 2+ years in financial analysis, FP&A, or data analytics.
  • Advanced Excel / Google Sheets (pivot tables, INDEX / MATCH, macros).
  • Proficiency in SQL for querying and joining datasets.
  • Experience preparing variance analyses and management reports.

    • Ideal Experience & Skills :

  • Python or R for advanced analytics and data modeling.
  • Experience with BI tools (Tableau, Power BI, Looker).
  • Industry background in SaaS, finance, healthcare, or professional services.
  • Familiarity with ERP systems (NetSuite, SAP, Oracle) for data extraction.

    • What Does a Typical Day Look Like?

    A Financial Analyst / Data Analyst's day revolves around turning raw financial and operational data into meaningful insights. You will :

  • Pull and clean data from ERP or SQL sources to prepare daily / weekly reports.
  • Update financial models with the latest actuals and run scenario analyses.
  • Prepare variance analyses to explain deviations from budget or forecast.
  • Build dashboards in BI tools to give leadership real-time visibility into KPIs.
  • Collaborate with stakeholders, presenting findings in clear, actionable terms.
  • Document assumptions and methodologies so models and analyses are transparent and repeatable.

    • In essence : you ensure decision-makers always have accurate, data-driven insights to guide strategy.

    Key Metrics for Success (KPIs) :

  • Accuracy of forecasts and financial models (variance within 510%).
  • Timeliness of monthly / quarterly reporting.
  • Reliability and clarity of dashboards delivered to stakeholders.
  • Positive feedback from leadership on insights and recommendations.
  • Reduced errors and improved data quality across reports.

    • Interview Process :

  • Initial Phone Screen
  • Video Interview with Recruiter
  • Practical Task (e.g., build a simple financial model or create a sample dashboard from dataset)
  • Client Interview with Finance / Operations Leadership
  • Offer & Background Verification
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