Marketing Data Scientist, Amazon

• You should have superb analytical, technical, business and communication skills to be able to work with marketing, business and technology leaders to define and prioritize key business questions, build data acquisition processes, data sets, statistical models and analyses that answer those questions
• This role requires an individual with deep marketing background, exceptionally strong quantitative modeling skills and experience using statistical methods to produce actionable customer insights
• The successful candidate will be a proven analytics leader who is comfortable with ambiguity, demonstrates strong attention to detail, and thrives in a fast-paced environment
• Experience with MMM modeling
• 2+ years of data scientist experience
• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• Experience applying theoretical models in an applied environment

Desirable

• Partner with senior business and technology leaders to develop data-driven business strategy
• Experience with marketing analytics concepts like marketing mix modelling, LTV modelling, payback analysis, regional tests, ROI analysis etc
• Proven ability to communicate complex technical work to a non-technical audience
• The ability to work with minimal guidance, be proactive and to handle ambiguity and the challenge of quickly evolving goals
• Deliver insights to help shape strategy across a wide spectrum of business and technology areas, including: customer acquisition, customer lifecycle, marketing and sales
• Lead research and development of foundational business enablers, including: acquisition and lifecycle stage propensity models, customer segmentation models, experimentation metrics, marketing attribution models, and forecast and lift models
• Oversee planning and execution of self-service analytics data infrastructure roadmap using Tableau- - Provide guidance and thought-leadership on analytical best practices to team members and business partners
• Build a Data Engineering team to build requirements for data infrastructure necessary to facilitate efficient analysis and reporting
• Translate analytic insights into concrete, actionable recommendations for business or product improvement
• Building robust tracking of our spend, subs, and revenue data that allows our marketing team to adjust their spend decisions over time
• Building predictive models that allow us to predict LTV and CAC over multi-year timeframes
• Building tools to allow us to measure the LTV impact from specific product experiments, to help product teams maximize impact for long-term LTV
• Helping us measure the impact of widely targeted brand spend on channels like TV and out-of-home
• Manage a roadmap for our marketing analytics measurement framework
• Conduct ad-hoc analysis and provide data expertise around attribution, LTV modelling, ROI analysis, and help uncover insights in our ads and user behavior that allow us to efficiently deploy millions of dollars in ad spend per month