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Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.
Summary Posted: Mar 1, 2022
Weekly Hours: 40
At Apple, new ideas have a way of becoming excellent products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish! The Product Marketing Analytics team is seeking a Sr. Data Scientist for Marketing Customer Analytics with deep experience in statistical modeling, consultative applied analytics, and decision support.
* Significant experience in logistic regression, with preference for experience also applying other modeling techniques including time-series regression (preferably mixed models), data classification and reduction (e.g. cluster)
* Fluency in Python, Spark, and R, with experience writing scripts that are part of a production-type analytic solution
* Proven technical database knowledge (Oracle, Teradata, Hadoop, data modeling) and experience optimizing SQL queries on large data.
* 1-2 years of experience working with Tableau.
* Passionately analytical and curious with strong out-of-the-box thinking
* Outstanding written, verbal, and presentation skills with the ability to develop and present conclusions and recommendation to senior executives
* Excellent project management and consultative skills
* Able to work effectively on sometimes ambiguous data and constructs within a constantly evolving environment, tight deadlines and priority changes
Support Marketing Communications, Product Marketing, and cross-functional business teams with analytics for database marketing, customer product and services engagement, and marketing campaign efficiency. Develop customer propensity models, with an emphasis on logistic regression, to optimize marketing communications, support cross-functional partners on personalization initiatives, and understand key drivers of customer behavior. Develop statistical models to analyze total market investments, to include base and promotional pricing, digital and traditional marketing mix, direct marketing attribution, channel and in-store investments, and partner media/pricing/program effects. Manage modeling projects through all phases, including data preparation, quality and integration, modeling, data visualization and presentation of results and deliverables. Collaborate with Engineering and Machine Learning teams to support building of a custom propensity modeling engine and pipeline. Develop highly polished and functional Tableau dashboards to support reporting, data discovery and statistical analysis for consultative projects and analytic capability development. Collaborate with business partners by conducting regular and ad-hoc business analysis and analytics to provide meaningful insights and decision support at tactical and strategic levels. Lead workflows, requirements and projects in collaboration with IT for analytic engineering tracks or ad hoc data model development
Education & Experience
Graduate degree required in Business (with quantitative emphasis), Statistics, Data Mining, Machine Learning, Analytics, Econometrics, Mathematics, Operations Research, Industrial Engineering, or related field