Hi,
I’m Victoria
Data Analyst. Python. R. SQL. Tableau. Looker. Math Games. Udemy Enthusiast. Dog Lover.
Professional Summary
I am a data analyst with expertise in utilizing analytical tools such as R, Python, SQL, and Looker to harvest and visualize data, identify patterns, and develop predictive models in order to enhance business decisions. Experienced in optimizing reporting efficiency through advanced automation techniques. Expertise in statistics and analytics, complemented by a strong ability to convert complex datasets into actionable insights. Committed to gathering, synthesizing and visualizing quantitative data, aimed at boosting efficiency and driving profitability.
My Interests & Skills
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Utilizing RStudio packages such as rvest and the tidyverse, or Python libraries like pandas and beautiful soup, I’m able to refine raw, unstructured data into well-organized formats. This includes meticulous gathering, cleaning, and transforming data into structured datasets that facilitate deeper analysis. By optimizing data readability and usability, I’m able to lead more effective data-driven decision-making.
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Raw figures can transform into insightful narratives and inform strategic decision-making by skillfully blending quantitative data with qualitative context. While numbers alone are merely informative, they can become strategic guides that propel businesses into clear pathways for growth and innovation.
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Have an every day task that is tedious? Let’s schedule that. Python stands as a beacon of efficiency in the modern digital landscape, automating the mundane and streamlining the complex. Automation not only accelerates workflows but allows for focus on innovation and strategy, pushing businesses toward efficiency and optimization.
Projects
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Churn Analysis
The churn prediction analysis focuses on identifying key factors that influence customers' decisions to discontinue services on the popular Telecom dataset. Key steps included preprocessing data, training ML models like logistic regression and random forests, and evaluating the mode using accuracy metrics and confusion matrices. Model features are then analyzed and applied in a business context.
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Local Animal Shelter EDA
I scheduled a daily scrape of the CMACC site to create a df of all dogs in the shelter’s system. I wrangle the data, cleaning and creating new variable, then look into patterns and trends in the data. Next, I create a dashboard that serves a tool to choose your next foster or fur baby and look at shelter data.
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Sushi Menu Wrangle
Ever needed help choosing off of a menu?
This project scrapes my favorite sushi restaurant’s menu, gathers it into a tidy df in R, then joins the data with Uber Eats data to see what items are most popular and liked.