Amazon is looking to define and prioritize key business questions, build data acquisition processes, data sets, statistical models and analyses to answer those questions, and provide actionable customer insights to shape business strategy.
Requirements
- 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
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience with MMM modeling
Responsibilities
- 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
- 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.
- Build a Data Engineering team to build requirements for data infrastructure necessary to facilitate efficient analysis and reporting
- 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
Other
- superb analytical, technical, business and communication skills to be able to work with marketing, business and technology leaders
- deep marketing background, exceptionally strong quantitative modeling skills and experience using statistical methods to produce actionable customer insights
- 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
- work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies.
