Job Description: Partner closely with functional leadership on designing measurement strategies and translate business requirements to define approach for complex opportunities such as lead attribution, segmentation, and customer lifetime value. Apply specialized data science methods (multivariate regression, classification, time-series modeling, survival/churn analysis, ANOVA/t-test, etc.) to construct advanced analytics instrumentation. Acquire, structuralize, and clean data from various marketing data sources; train, tune, and evaluate statistical methods & best practices to build and deploy end-to-end pipelines for productionized machine learning models at scale. Take ownership and provide oversight for predictive models’ lifecycle, maintain integration of predictions to CRM and media platforms, monitor accuracy performance, measure impact, advise strategies, and communicate insights to Marketing partners, Admissions partners, and leadership. Extract, develop, and own properties of data governance system through API connectors to provide a seamless data ecosystem for Marketing and Admissions. Leverage a variety of scripting languages (R, Python, Javascript) and SQL to pivot and transfer large data objects, create transformations for tests and analyses, and implement automated and self-serving dashboarding capabilities. Integrate platform data aggregations and dive deep into Marketing and Admissions metrics to perform hands-on analyses, produce holistic intelligence, develop insights and recommendations to inform decisions across business functions. Create visualizations and design dashboards to measure performance of marketing channels, identify optimization opportunities and pain-points in student decision journeys. Conduct ad hoc marketing analytics and provide data interpretation, advise Marketing and Admissions teams on quantitative solutions. Telecommuting is permitted from any location in the United States. Other Job Requirements: Qualified candidates must have a Master’s Degree or foreign equivalent in Data Analytics, Computer Science, Statistics, Mathematics, Quantitative Management or related field and at least 1 year of experience. Experience must include the following: Data science methods including multivariate regression, classification, time-series modeling, survival/churn analysis, ANOVA/t-test; Development of end-to-end machine learning solutions; SQL; BigQuery; R and Python programming languages; Working with disparate data sets, sources, formats; Domo, Tableau, Microsoft Power BI, and Data Studio BI tools; Using various techniques to transform data at scale; Google Analytics 360 (both GA Universal and GA4); Google Ads and Facebook Ads digital advertising platforms; Deep knowledge in CRM and Marketing automation data (Salesforce CRM, Salesforce Marketing Cloud, Marketo, Eloqua). Contact: Send resume to Erika De Jesus at edejesus@apei.com (Ref. No. L2285)