QualificationsStatistical analysisSQLSASMentoringDigital marketingBachelor’s degreeMaster of Business AdministrationDoctoral degreeMaster’s degreeDoctor of Philosophy
Partner with marketing, research, and product organizations to scope, design, execute, measure, and improve the impact of marketing efforts on the NA business
Develop quantitative analysis, tools, ad-hoc reports, and models to support marketing decision making. Have experience in measuring digital marketing KPIs, ROI, marketing effectiveness, LTV, ROAS, sentiment analysis, etc.
Help create, maintain, and improve key data sets, pipelines, and reporting to track and manage NA GBM activities
Project manage improvements to measurement methodologies, products, and approaches in the NA region
Drive end-to-end insights creation-to-consumption lifecycle, leading business problem definition, hypotheses formulation, designing and delivering the solution to support business decisions and outcomes
Build new metrics, dashboards and insights to measure GBM’s marketing activities in order to optimize and scale their actions
Translate data insights into actions and recommendations that will drive marketing effectiveness and tell the story to executive audiences on user growth, marketing performance and product adoption
6+ years of work experience in Data Science, Marketing Analytics, Product Analytics Consulting, Decision Science and/or Business Analytics or 4+ years of experience with MBA/Master’s
4+ years experience in SQL
4+ years experience in applying statistical techniques in a business and/or marketing context using R, Python, SAS, SPSS, MATLAB
4+ years of experience in building business facing visualizations and dashboards
Experience in experiment design, hypothesis testing and statistical analysis
Experience leveraging data driven models to drive business decisions and building visualizations using large datasets and multiple data sources
Experience working with multiple marketing and digital marketing teams directly to influence and shape campaign measurement, analytics frameworks and drive decision-making
Knowledge of statistics and optimization techniques. Hands-on experience with large datasets (i.e. data extraction, cleaning, modelling, interpretation and presentation)
Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
MBA/MS/PhD degree in a quantitative field
Experience managing and prioritizing multiple concurrent projects and driving initiatives in a large cross-functional environment
Experience in a consumer technology company
Experience guiding and mentoring junior analysts
Experience operating within globally distributed teams
Experience developing data pipelines via SQL and Python-based ETL framework
Experience shipping code into production
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