About the job
Fire TV is reshaping the way millions of people discover, engage with, and enjoy entertainment every day. The Fire TV, Advertising and Appstore Decision Science organization is looking for a Data Scientist who is passionate about using data to surface customer insights that will influence the development of new and improved customer experiences across the Fire TV organization. This role contributes to the foundational science and analytics capabilities used by Product, Finance, Marketing, Advertising, and Engineering teams to make high-quality business decisions. You will design, develop, and operationalize data science solutions supporting Fire TV customer engagement and retention, lifecycle analytics, Ads monetization, experimentation, and AI-enabled analytics.
Responsibilities
- Design, develop, validate, and maintain machine learning models, statistical analyses, and decision frameworks supporting one or more of the following pillars: Fire TV engagement, lifecycle analytics, ads monetization, and Appstore performance
- Independently own data science workstreams with guidance on ambiguous or high-impact decisions. Deliver analyses and models from problem definition through validation and handoff, partnering with senior scientists and stakeholders as needed
- Build and refine customer segmentation and clustering frameworks that enable personalized marketing and engagement strategies
- Contribute to the design of A/B experiments and analyses; develop power analyses, define guardrail and success metrics, and interpret results to inform product decisions
- Partner with Business Intelligence Engineers, Data Engineers, Product, Finance, and Marketing stakeholders to translate business questions into rigorous analytical frameworks
- Identify and close measurement gaps — including coverage gaps in customer attribution, engagement, and conversion — and advocate for better instrumentation upstream
- Communicate findings clearly and accurately to both technical and non-technical audiences; write rigorous technical documents and present results with appropriate caveats
- Contribute to DS best practices including reproducibility, code quality, documentation, and model validation standards
- Mentor junior data scientists and analysts on methodology, tool usage, and analytical approach
Qualifications
Minimum
- 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
- 2+ years of data scientist experience
- Bachelor's degree
Preferred
- PhD in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- Experience in A/B testing
- Experience working on multi-team, cross-disciplinary projects
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience with AI/ML technologies
- Experience effectively communicating complex concepts through written and verbal communication
- Experience with clustering, propensity modeling, time series modeling, or demand forecasting
- Experience mentoring or providing technical guidance to junior scientists or analysts