Associate Director, Analyst (5 Open Positions)
Cincinnati, Ohio and various unanticipated work locations
Applies marketing research and analytics knowledge to assess client needs and business objectives. Creates meaningful and actionable analysis using client and customer data. Applies data mining and statistical analysis techniques like hypothesis testing, segmentation, trend analysis, and modeling to analyze customer data using SAS to develop best, most efficient solution. As analytical lead, interacts with key client contacts, forges relationships with internal and external clients and proactively provides recommendations that drive incremental value. Makes recommendations regarding resource planning and project scoping. Develops project briefs and scoping documents for internal and external clients. Delivers presentations and insights to internal and external clients. Provides mentorship to other team members and serves as internal analytic lead across functional departments. Uses statistical and database software packages like SAS and SQL to create new code to manage data and draw customer insights.
Master's degree or foreign educational equivalent, in Mathematics, Economics, Quantitative Analysis, Industrial Engineering or other relevant discipline plus two years of experience (gained at any time): as a data analyst responsible for analyzing large retailer customer data to produce actionable recommendations; conducting data analysis to include the design, test, and implementation of analytical work plans that allow for better strategic business decisions.
Included must have been 1 year of experience: using SQL language and SAS, BASE, STAT and Macros to manipulate data from large databases to summarize data and perform detailed statistical analysis to derive insights and create summaries of data for detailed analysis for retail or CPG clients; translating analytical results into business and marketing solutions and communicating and presenting the results and recommendations to the key internal and external stakeholders using applications like Excel, Word, PowerPoint; working directly with business partners and retail or CPG clients to design marketing analyses, manage projects and manage client and partner expectations; applying data mining and statistical analysis techniques such as regression, clustering, dimensionality reduction, forecasting and behavior-based analytics using SAS and SQL to make actionable recommendations for retail or CPG clients; and, serving as internal analytic lead within or across functional departments of company.
dunnhumby is the world’s leading customer science company. We analyse data and apply new insights from more than 400 million customers...