We'd Love to See:Job Description
Statisticians for various and unanticipated worksites throughout the U.S. (HQ: Chicago, IL). Responsible for statistical analytics, including marketing and media mix modeling, predictive analytics, and market forecasting. Build marketing mix models that are based on statistics, econometrics, and machine learning techniques such as hierarchical Bayesian, ridge regression, and clustering algorithms. Involved in practical analytics to generate actionable marketing insights to aid in marketing decisions. Analyze data sets to generate insights on paid media, market conditions, and individual activities of the consumer journey. Perform data validation, visualization, cleaning, and restructuring using R programming language. Estimate marketing impact and efficiency, return on investment, marginal return on investment, brand equity, profit, and market share. Translate technical language into easy to understand concepts for presentations to clients. Technical environment: Marketing mix modeling, predictive analytics; machine learning techniques; R, Python, SQL; hierarchical Bayesian regression, Ridge regression; clustering algorithms.
Master’s degree in Statistics or Analytics or a related field plus one year of experience in the job offered or in statistics required. Required skills: experience with machine learning techniques, Marketing mix modeling, hierarchical Bayesian regression, Ridge regression; clustering algorithms, translating tech language into easy to understand concepts for presentations to clients. Telecommuting permitted.