Responsible for advanced predictive analytics within the Marketing Department. Functional responsibilities include developing predictive models, customer segmentation, marketing optimization, and quantitative market research.
Essential functions of the position:
Lead advanced predictive analytics projects (response, churn models) using cutting-edge data mining and statistical modeling techniques.
Develop and execute testing and optimization schemes for ongoing marketing campaigns.
Identify customer analytics opportunities and decompose marketing strategy into ideas and specific projects for model development and execution.
Manage dataset creation and data quality control processes for analytics and model development and validation.
Establish model validation and scoring process, and manage model inventory and documentation.
Develop and communicate business-driven analytic solutions and capabilities, translating modeling and analytic output into understandable and actionable business knowledge.
Evaluate and enhance modeling process (requirements, design, implementation and measurement) of predictive models, segmentation and other statistical techniques.
Provide expertise in modeling, optimization, and data visualization, and introducing new methods and tools to drive analytic innovation.
Conduct strategic customer analysis and other quantitative market research to support marketing initiatives.
Identify and execute advanced analytical opportunities to continually improve knowledge of customer behaviors and trends, and to drive customer acquisition, retention and loyalty strategies.
Provide data analytics subject matter expertise and collaborate with other analytic groups across the organization to share best practice and methods.
Secondary functions of the position:
Strong knowledge of statistical/econometric models, advanced data mining and predictive modeling techniques.
Statistical programming software experience is required (SAS, R, Matlab, SQL).
Hands on experience and expertise in linear/non-linear regression models, time series model, survival analysis, cluster analysis, factor analysis, marketing mixed modeling, and optimization.
Strong business acumen and previous experience with process improvement as it relates to model building, automation, validation, or other statistical methods.
Excellent oral and written communication skills. Ability to communicate ideas and analysis results effectively to both technical and non-technical audiences.
Education and Experience:
Graduate degree in Statistics, Economics, Operations Research, Mathematics, Computer Science or related quantitative field.
4+ years of experience with statistical modeling and data mining using large and complex datasets.
Hyundai is an Equal Opportunity Employer M/F/D/V.
Hyundai Capital America - 12 months ago