Data Analyst
CurrentPerforming numerous types of projects centered around data. First is converting unstructured data in the form of Excel files, CSV, PDF, TXT, XML, etc. into a single structured table on SQL or multiple tables on SQL that use primary keys, and foreign keys to describe relationships between variables. Example file types I have run this task on is EDI 880 Invoices. These required 4 SQL tables to make the data easy to understand: Header, Header Allowances, Details, Detail Allowances. These invoices were originally txt files. This project contained about 106,000 invoices over the course of 12 months, and is used daily to perform audits for our client.Second is utilizing my skills in data science to optimize the price our clients should sell their products. This requires using SQL to gather the data, and then Python to first perform exploratory data analysis to search for trends, current margins, number of products sold and more. After exploration is complete, use machine learning algorithms including but not limited to Linear Regression, Random Forest, CatBoost, KNeighbors, XGBoost to read the data and then make predictions on if a product is sold for a new set of prices, how many of that product would I be expected to sell? Then, take those expected quantities at each price and find where the expected margin is maximized. A sample product I performed this task for was Cheetos Mac & Cheese as this is a product that many families with young kids may or may not buy depending on the price of the product, and the time of year, so the optimal price takes into account the season, and vendor price for optimization.
