The F2 FINDS team at Amazon is looking for a Data Scientist to generate actionable insights at scale from nuanced datasets to guide leaders on impactful business decisions and empower the highest standards of excellence for global operations.
Requirements
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 4+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team
Responsibilities
- Support the development of continuously-evolving business analytics and data models, own the quantitative analysis of the performance of our product/program discovery, models, science features, partner teams.
- Continually develop new ways of using data to look around the corners of the Retail business
- Use machine learning, data mining, and statistical techniques to design/run experiments that solve complex business problems.
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
- Develop a deep understanding of sales metrics, reporting tools, and data structures in order to identify and drive resolution of issues, provide actionable intelligence with existing metrics or identify, develop, and propose new metrics, dashboards, scorecards or new tools.
- Develop relationships and processes with partner teams, PMs/TPMs, engineers, and other functional teams to identify and address reporting issues.
- Manage and develop advanced analytical tools that align, and simplify, monthly business reviews, annual planning, and forecasting processes.
Other
- Bachelor's degree
- Ability to communicate complex and nuanced messaging to a diverse audience of senior leadership stakeholders
- Work-life harmony and flexibility as part of the working culture
- Inclusive team culture and diversity
- Mentorship and career growth opportunities
