Responsibilities: The Marketing modeling team is responsible for providing support for customer analytics, marketing optimization, marketing operations including test plans, campaign testing, suppression and segmentation, assisting in modeling and campaign analytics. The successful candidate has a proven track record in customer analytics, predictive modeling and database marketing capabilities. This role will require the ability not only to set and deliver against the overarching strategy, but also to be an active contributor to the daily workload and tactical activities. Customer analytics supports all areas of the customer marketing organization. This is an outstanding opportunity for a motivated, strategic thinker with practical hands-on ability to build upon a talented foundation and to take the customer analytics capability to new heights at The Children's Place. Responsible for analytical support and statistical modeling for the purpose of maximizing revenue. Accountable for driving valuable fact-based and quantitative consumer insights from internal systems and to synthesize key findings which inform business and strategic marketing strategies. Customer Analytics: Develop customer profiles and customer segmentation. Create predictive and behavioral models. Continuously validate and optimize models as well as the customer profiles and segmentation work. Marketing Optimization: Conduct analytics for A/B and multivariate tests, create business cases, strategies and prepare forecasts and related models. Campaign and Channel Analytics: Design the measurement plan, ensure tracking enablement and complete and distribute all campaign and channel results as well as ROI reporting. Share insights and optimization recommendations widely with all internal customers. Continually review and make recommendations for the improvement of our processes and technology in order to build a more quantitative and data-driven approach to customer marketing. Codify and distribute formal frameworks and methodologies in support of data-driven marketing methodologies. Support the production of analytical studies, customer models and deliver accurate customer based insights on spending behavior, response & predictive modeling, scoring, forecasting, customer lifetime value, and other data sources compiled from multiple tools and sources. Ensure valuable model insights are evaluated for long-term reporting utilization. Performs duties by collecting data, analysis, and makes recommendations to management relevant to the strategic direction of marketing programs. Analyzes market conditions, sales trends, customer preferences and competitive behavior. Participate as a thought leader or lead large strategic projects from scope definition through to execution and implementation. Expert level programming skills using SAS, R or Python as a programming language to meet the challenges of advanced data manipulation, complicated programming logic, and large data volumes is required. Minimum three years or equivalent experience of SAS programming using SAS/BASE, SAS/MACRO, SAS/SQL, SAS/STAT, and SAS/GRAPH, SAS Stored Processes in a data intense environment. Experience with SAS Enterprise Guide, SAS Marketing Automation, SAS Data Integration Studio, Enterprise Miner, SAS Web Report Studio, SAS OLAP and SAS Information Map Studio is highly preferred. MS office products and SQL is required Assist director and manager of analytics and marketing in promoting and developing a strong sense of analytics culture based on data facts, teamwork, contribution Education and Experience: Master's degree in mathematics, statistics, or related field 3-5 years in analytics role including experience in advanced analytics (statistical modeling) Experience working with transaction level, email, and customer data strongly preferred Retail industry experience preferred Skills and Behaviors: Ability to manage internal and external resources Strong working knowledge in one or more analytics tools such as SAS, R, Python Strong working knowledge in Adobe Solid understanding of page tagging concepts Proficient in Google Analytics (Preferred) Strong understanding of marketing, user experience, and customer segmentation principles, best practices and analytical approaches Ability to apply digital marketing analytics results to the practical considerations of day-to-day marketing and operational business challenges Understanding of machine learning techniques such as Regression, ANOVA, Clustering, Decision Trees, Random Forests, Gradient Boosting Machines Strong knowledge in online and offline experiments, including A/B testing and multivariate experiments Familiar with recommendation systems and algorithms Ability to analyze, interpret, and develop insights from complex data structure Ability to tell the story focuses on insights, not just data R000008410Salary Range: NAMinimum QualificationLess than 5 years Associated topics: computer engineering, information technology, java, optical, photonics, processor, programmer, python, robotics, schematic
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