Director, Advanced Analytics
Interested in taking advantage of the sizzling hot analytics job market this summer season? We’ve got you covered. A leading market research and insights firm has an opening for a Director to join their team in the greater Chicago area. As a member of the company’s centralized modeling and analytics group, you will collaborate with cross-functional teams to conduct quantitative research studies and analyses and work to improve analytics processes and methods.
This is a blended role that will involve hands-on analytics and statistical modeling in addition to presenting insights, so strong technical and communication skills are essential. The Director will manage projects for clients end to end, working directly with leading brands in the food, consumer goods, and retail industries. You will leverage point-of-sale and consumer retail data to build customized research projects to help clients answer their most pressing business and marketing questions.
Qualified candidates will bring:
- Degree in Econometrics, Statistics, or related quantitative field (Master’s or higher preferred)
- 8+ years’ experience with marketing analytics, ideally within the food or CPG industry
- Previous hands on programming experience with SAS, SQL, and R
- Ability to translate technical material for a non-technical audience
- Excellent interpersonal and communication skills
- Ability to work seamlessly with others
- Prior experience with point-of-sale data preferred
A seasoned, communicative analytics professional who is results driven will thrive in this role. If you’re looking for the chance work with well-known brands in both a strategic hands-on analytics capacity, let’s chat.
Keywords: pricing elasticity, portfolio pricing, forecasting, valuation, optimization, promotional analytics, market mix modeling, ROI analysis, segmentation, advertising effectiveness, optimal assortment, modeling, data management, research, statistical modeling, statistical analysis, SQL, R, SAS, regression, driver analysis, Java, Python, discrete choice, Bayesian methods, time series analysis, CHAID analysis, factor analysis, cluster analysis