3+ years of analyzing and interpreting data with redshift, oracle, nosql etc. experience
- experience with data visualization using tableau, quicksight, or similar tools
- experience with data modeling, warehousing and building etl pipelines
- experience in statistical analysis packages such as r, sas and matlab
- experience using sql to pull data from a database or data warehouse and scripting experience (python) to process data for modeling
key job responsibilities
- lead analytics and insights efforts for a specific amazon music program
- work as the internal lead analytics consultant for marketing teams and collaborate on long-term strategy together
- define and deliver reporting and visualization that supports the analytical needs of internal business leaders
- drive self-service solutions for senior business stakeholders informing marketing investment decisions
- use analytical insights to help increase business and teams effectiveness against key strategic goals
- build a thorough understanding of the streaming music industry, the subscription business model, and key internal partners across prime, amazon devices, media and entertainment businesses
- partner with analytics and science teams across amazon entertainment and subscription businesses
- educate and evangelize across internal teams on analytics, insights and measurement by writing whitepapers and knowledge documentation and delivering learning sessions
about the team
the data, insights, science and optimization, marketing & growth (disco m&g) team is looking for a business intelligence engineer to join a team of data scientists, analytics leads, business intelligence engineers and data engineers who analyze big data, provide analytics and insights as well as build models and algorithms that power "hands off the wheel" (hotw) marketing for personalized experiences.
disco m&g team focuses on accelerating amazon music customer growth by empowering marketing & growth teams to make sound, customer-centric decisions through data and insights.
we build data pipelines, self-service analytics, insights and predictive models enabling acquisition, engagement and retention at scale with personalized customer touchpoints.
- experience with aws solutions such as ec2, dynamodb, s3, and redshift
- experience in data mining, etl, etc. and using databases in a business environment with large-scale, complex datasets