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LanaGeis/README.md

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Hi, I'm Lana Geissinger

Financial & Data Analyst | Power BI Reporting | SQL | Python | R

I am a Financial Billing Analyst with 17+ years of experience across finance, billing operations, revenue analytics, and business reporting. I build Power BI dashboards, automate recurring reporting workflows, and turn complex financial and operational data into clear, KPI-driven insights for business and executive decision-making.

Focus: Financial analysis • Power BI reporting • Revenue and billing analytics • KPI development • Reporting automation • Data storytelling


What I Bring

  • Deliver Power BI dashboards and executive-ready reports that make performance easy to monitor and act on
  • Analyze financial and operational data to identify trends, variances, risks, and opportunities
  • Develop KPI scorecards and reporting frameworks that align metrics with business priorities
  • Translate stakeholder questions into practical data requirements, metrics, visuals, and actionable insights
  • Improve reporting consistency through streamlined, repeatable workflows and data-quality-focused analysis

Analytics & BI Toolkit

Area Skills
Power BI Data modeling, DAX, Power Query, dashboard design, drill-through reporting, KPI scorecards, paginated reporting
SQL Data extraction, joins, aggregations, transformations, and metric logic
Python pandas, exploratory data analysis, data cleaning, transformation, and visualization
R Statistical analysis, visualization, and exploratory analysis
Business Analytics Financial reporting, revenue and billing analytics, variance analysis, trend analysis, root-cause investigation
Reporting Tools Excel, Tableau, Jupyter Notebook, RStudio, Git/GitHub

Featured Projects

Workforce analytics project using BLS and O*NET data to examine AI and automation impacts on jobs.

  • Built Python workflows for data preparation, cleaning, and trend analysis
  • Developed Power BI dashboards to communicate workforce shifts and risk patterns
  • Presented findings through clear visual narratives to support strategic workforce discussions

Reusable Power BI reporting solution for structured paginated-report exports to Excel.

  • Designed a repeatable workflow for operational reporting distribution
  • Supported consistent, business-friendly Excel output from Power BI paginated reports
  • Demonstrated scalable reporting design aligned with recurring business processes

Exploratory analysis of 140 years of historical naming data.

  • Cleaned, structured, and analyzed long-range data in Python
  • Identified trend cycles, popularity shifts, and generational patterns through visualization
  • Translated raw data into a concise, narrative-driven analytical story

NLP project focused on identifying misconception patterns in open-ended student responses.

  • Applied TF-IDF, embeddings, and classification techniques to text-based data
  • Explored patterns that can help surface misunderstandings at scale
  • Connected model outputs to practical interpretation and insight generation

Professional Background

  • 17+ years in finance, billing operations, revenue analytics, and business reporting
  • Strong foundation in financial analysis, reconciliations, performance monitoring, and data-driven decision-making
  • Experienced in communicating analytical findings to both technical and non-technical stakeholders
  • Master’s in Data Science in progress, with bachelor’s degrees in Economics and Management and Accounting

Languages & Tools

Power BI SQL Python R pandas Excel Tableau GitHub


Connect

LinkedIn

Open to Financial Analyst, Data Analyst, Business Intelligence Analyst, Revenue Analyst, and Power BI-focused opportunities where analytics supports measurable business outcomes.

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  1. Employment-Trend-Analysis Employment-Trend-Analysis Public

    A milestone-based data science project exploring how automation and AI affect U.S. occupations and skills. Data collected from BLS, O*NET, and other sources, cleaned and merged into SQLite, with an…

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  2. US_baby_names_exploration US_baby_names_exploration Public

    A 140-year analysis of naming patterns, cultural shifts, and generational trends using the SSA dataset. Features data cleaning, Matplotlib visualizations, and exploratory analysis.

    Jupyter Notebook

  3. MAP-Student-Math-Misunderstandings_Kaggle MAP-Student-Math-Misunderstandings_Kaggle Public

    NLP + Machine Learning project identifying student math misconceptions using open-ended responses. Includes TF-IDF, embeddings, logistic regression, deep learning baselines, and full model evaluation.

    Jupyter Notebook