AOP FC Analytics team manages a suite of MIS reporting published at a various regular frequency, productivity tools to bridge the current software challenges and serve all analytical needs of leadership team with data & analysis.
The ideal candidate relishes working with large volumes of data, enjoys the challenge of highly complex business contexts, and, above all else, is passionate about data and analytics. The candidate is an expert with business intelligence tools and passionately partners with the business to identify strategic opportunities where data-backed insights drive value creation. An effective communicator, the candidate crisply translates analysis result into executive-facing business terms. The candidate works aptly with internal and external teams to push the projects across the finishing line. The candidate is a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail), and enjoys working in a fast-paced and global team.
Key job responsibilities
§ Interfacing with business customers, gathering requirements and delivering complete BI solutions to drive insights and inform product, operations, and marketing decisions.
§ Interfacing with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL (Redshift, Oracle) and ability to use a programming and/or scripting language to process data for modeling
§ Evolve organization wide Self-Service platforms
§ Building metrics to analyze key inputs to forecasting systems
§ Recognizing and adopting best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
- 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)
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
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