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Key job responsibilities
Enable decision-making by conducting analyses from multiple sources to present research in a digestible and actionable format.
• Analyze large data sets using a variety of query and visualization tools.
• Provide technical expertise in 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.
• Provide mentorship and coaching for embedded analysts and other business teams.
• Clearly communicate any potential discrepancies and/or reporting downtime, including specific root cause, steps to resolution, and resolution date to a large end-user base.
• Work with subject matter experts to document and translate business requirements into technical requirements.
• Manage multiple projects and proactively communicates issues, priorities, and objectives.
• Work with subject matter experts to document and translate business requirements into technical requirements.A day in the life
You will develop executive dashboards, run ad hoc analysis focussing on growth, and build a data quality framework. 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 research
- 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
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