This job is with Amazon, an inclusive employer and a member of myGwork the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.
Description
Come build the future of smart security with us. Are you interested in helping shape the future of devices and services designed to keep people close to what's important
About Ring
We started in a garage in 2012 when our founder asked a simple question: what if you could answer the front door from your phone What if you could be there without needing to actually, you know, be there After many late nights and endless tinkering, our first Video Doorbell was born.
That invention has grown into over a decade of groundbreaking products and next-level features. And at the core of all that, everything we've done and everything we've yet to build, is that same inventor's spirit and drive to bridge the distance between people and what they care about. Whatever it is, at Ring we're committed to helping you be there for it.
The Business Intelligence Engineer, Ring Data Science and Engineering BI team will develop models and tools, conduct statistical analyses, evaluate large data sets, and create tailored models and dashboards. Additionally, you will be instrumental in the creation of a reliable and scalable infrastructure for ongoing reporting and analytics. You will be structuring ambiguous problems and designing analytics across various disciplines, resulting in actionable recommendations ranging from strategic planning, product strategy/launches, and engineering improvements to marketing campaign optimization, customer servicing trending, and competitive research.
Key job responsibilities
- Enable decision-making by retrieving and aggregating data from multiple sources to present it in a digestible and actionable format
- Work with the ios and Android development and product teams to identify gaps and trends.
- Analyze large data sets using a variety of database query and visualization tools
- Provide technical expertise in extracting, integrating, and analyzing critical data
- Anticipate, identify, structure, and solve critical problems
- Design and develop key performance metrics and indicators using standardized and custom reports
- Perform ad hoc analysis to quickly solve time sensitive operational issues and business cases.
- Clearly communicate any potential data discrepancies and/or reporting downtime, including specific root cause, steps to resolution, and resolution date to a large end-user base
- Partner with subject matter experts to document and translate business requirements into technical requirements
- Manage multiple projects and proactively communicates issues, priorities, and objectives
- Clearly communicate any potential data discrepancies and/or reporting downtime, including specific root cause, steps to resolution, and resolution date to a large end-user base
- Partner with BI architects to provide valuable inputs to remodel the existing data warehouse.
About The Team
The Ring Data Science and Engineering (RDSE) Org is responsible for the data strategy, architecture, governance, science, and software services Ring teams use to inform business strategy or power experiences with data. The central Data Science and Analytics team (within RDSE and the team where this role is based) is responsible for core business metrics, shared data models, AI/ML models, business intelligence dashboards, and business analysis/science support.
Basic Qualifications
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)
Preferred Qualifications
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
