Thanks to visit codestin.com
Credit goes to github.com

Skip to content
View LanaGeis's full-sized avatar

Block or report LanaGeis

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don't include any personal information such as legal names or email addresses. Markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
LanaGeis/README.md

LanaGeis

πŸ‘‹ Hi there!

I'm Lana β€” a data enthusiast transitioning from finance into data analytics and data science.

  • πŸ’Ό With 15+ years in finance and business operations, I bring strong analytical thinking and data-driven decision-making.
  • πŸ“Š Currently mastering R, Python, SQL, and Power BI as part of my data analytics journey.
  • πŸ“š Pursuing a Master’s in Data Science to deepen my expertise in machine learning, statistics, and modern analytics.
  • πŸ” Passionate about uncovering insights that support smarter business strategy and operational efficiency.
  • 🌱 Continuously learning β€” from data wrangling and visualization to predictive modeling and NLP.
  • 🀝 Open to collaborating on data projects and connecting with others in analytics or tech.
  • πŸ’¬ Ask me about finance analytics, Excel automation, or turning messy data into actionable insights!

πŸ“« How to reach me: LinkedIn


Projects


πŸ› οΈ Languages & Tools

Python R SQL pandas seaborn ggplot2

Power BI Tableau Excel Microsoft Office

Jupyter RStudio PyCharm GitHub

Pinned Loading

  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…

    HTML

  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