About Me
Hi, I'm Vander.My journey in the world of data is driven by a curiosity to explore patterns, solve problems, and tell compelling stories through numbers. From raw data to actionable insights, I enjoy transforming information into knowledge.I have expertise in assisting companies and researchers with analyzing and visualizing their datasets. I am skilled at many data-science steps: data pre-processing, application of statistical methods, data visualization and results communication.I have worked in the field of data science for renowned research institute Stanford University and private companies like Spring Fertility. I also have expanded my skillset with tech accelerator OSLabs.I'm able to handle diverse datasets and deliver robust analytical solutions with particular expertise in SQL, Python, Tableau and Excel.Please feel free to connect with me.
Skills
Excel | Tableau | Power BI | SQL | Python
Data Visualization - 6+ years
Statistical Analysis - 4+ years
Report Development - 6+ years
Database Management - 5+ years
Featured Projects
Tableau
U.S. Food Recall Dashboard
Built an interactive Tableau dashboard that allows for analysis of annual U.S. food recall trends.
Python
Marketing Conversion
Created a dataset and visual analysis utilizing Python libraries Pandas and Matplotlib.
Excel
Coffee Bean Sales
Product performance analysis and visualization for coffee beans sales over multi-year period.
Tableau | U.S. Food Recall Dashboard
Over 80% of food recalls in the U.S. are not publicized. With this Tableau dashboard you can explore the staggering amount of recalls that have been reported to the FDA since they formed the public database, FDA Recall Enterprise System, in 2004. This dashboard highlights the geographic origins of recalls and showcases the which locations generate the most severe (Class III) recalls.
Dashboard Breakdown:
- Filters are dependent on each other and adjusts based on selections.
- Core KPI's at the top, beside the filters.
- Bar chart for visual of recalls classification breakdown for each state
- Heat map to show which states are hot zones for food recalls
- Line chart to show trends of recalls over time.View dashboard hereAll data recieved from openFDA food enforcement reports API. Last updated 12/2023.
Excel | Coffee Bean Sales
In December of 2022 I volunteered to assist a coffee retailer I frequented with evaluating their online sales. As this was a place I enjoyed dearly I was very interested in taking a closer look at their online marketplace so they can continue to grow and supply delicious mocha.Here are a few takeaways:
- Liberica was their most popular coffee type
- U.S. buyers make up a vast majority of their total sales
- January continually has an above average number of sales, most notably in 2022.
- Majority of sales were from small purchases as the largest buyer only accounted for less than 1% of salesThe dashboard is completely dynamic and adjusts depending on the month(s) selected via the slicer.
I used the following skills to maniuplate the data and create the dashboard:
- Pivot Tables
- Slicers
-Timeline
- SUMIFs
- Data Manipulation
- Aggregate FunctionsThe data was provided by coffee retailer and all identifying information was replaced with dummy data.
Python | Marketing Conversion
Created a dataset and visual analysis using Pandas and Matplotlib.First, I created the dataset using the Pandas library. This gave me 1,000 rows of random marketing data detailing sales conversion rates.
After looking through the newly created data, I wanted to answer the following:
1 | Conversion rate by traffic source
2 | Conversion rate by device type
3 | Conversion rate by geographic region
4 | Time series analysis depicting sales over timeI then created visualizations to answer each of the 4 prompts using the Matplotlib library.
And here are the visualizations generated by the script:
The visualizations resulted the following analysis:
1 | Social Media had the highest conversion rate.
2 | Most conversions were made on desktops.
3 | All 3 regions had very similar conversion rates.
4 | Most conversions were made at the end of August.