Every engagement starts with a conversation about what you're trying to decide. The method follows from the question, not the other way around.
You have data but no clear picture of what's in it. We clean and prepare the dataset, run exploratory analysis to surface patterns and outliers, and deliver a written summary of what the data actually supports, including what it doesn't. Typical inputs: spreadsheets, database exports, survey results. Typical output: a findings document with supporting charts.
You need people in the organization to see the numbers without asking you first. We build Power BI dashboards connected to your data sources, define the metrics and KPIs that matter for your decisions, and set them up so they refresh without manual work. Typical output: a working dashboard plus documentation on how the metrics are calculated.
You need an answer that holds up when someone challenges it. This covers regression and multivariate modeling, hypothesis testing, survey and experimental design, and review of existing analysis. We also collaborate on research projects and co-author statistical articles for publication, providing the methodological and analytical work alongside your subject-matter expertise.
You want to know what's likely to happen next, or which customers to focus on. We build forecasting models, customer segmentation, and classification models, then validate them honestly and tell you how much confidence the results deserve. Typical output: a working model, performance metrics, and a plain-language explanation of what it can and can't predict.