Sr. Data Analyst
CurrentOur team works on the “direct to consumer” side of Columbia’s business, both from an Ecommerce and Brick & Mortar perspective. My tasks range from quick one-off questions to deeper multi-month research projects leveraging data from ADW, the Azure Data Lake, up through local files.Some of the analysis themes I have worked on include:o Promotion Success- profitability, traffic impacts, conversions, click-through metrics, etc.o Market Basket- products being bought together, their frequencies, time trends, etc.o Weather Analytics- forecasting events that are statistical outliers for locations, machine learning predictive impacts to sales based on daily weather, etc.o Returns & Exchanges- highlighting consumer tendencies to reduce revenue losso Return Reserves- building machine learning experiments to forecast returns by segmentationSkills and Tools Leveraged:o PowerBI Desktop and Serviceo SQL querying and table managemento Python: PySpark and Pandaso Databricks Notebooks, Jobs and AutoML