Description
Are you passionate about driving business and customer impact through thoughtful analysis and data-driven insights? Are you a scientific thinker and a deeply technical individual who enjoys working with customers to transform how a business operates? Are you a builder that excels with ambiguity? We are looking for a Business Intelligence professional to drive our analytical revolution in the Talent Acquisition (TA) space. You will have the opportunity to work on a ground-up rebuild of our analytical capabilities, from data ingress to building models to measure performance metrics to end-user reporting and beyond. In this role, you will invent and build on behalf of candidates, experiment and test new ideas, evangelize successes, and drive consistency.
The ideal candidate is an independent Business Intelligence practitioner who can source data, cleanse, analyze, refine, enrich, model, present, automate, and document their findings. You will always be on the lookout for ways to optimize the information flow process, stay on top of the latest trends in Business Intelligence and Data Warehousing, and be able to coordinate and work on multiple, related projects.
Responsibilities:
• Provide data-driven, actionable insights to TA Leadership & Line Management
• Develop and Maintain Talent Acquisition scorecards, dashboards, and reports for use across ATA (and scalable Amazon-wide when possible)
• Design, develop, and evaluate statistical models (Clustering, Classification, Regressions, Time Series, et cetera)
• Establish scalable, efficient, and automated data processes
• Provide ad-hoc analytical support for TA Special Projects
• Develop and maintain relationships with key customer groups such as: TA Executive Leadership and 1st/2nd line Recruiting Management
• Develop User Stories and drive functional requirements gathering
Basic qualifications:
• Bachelor’s degree or higher in a quantitative/technical field (e.g. Computer Science, Information management system, Engineering)
• 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:
• Experience working with large-scale databases and data warehouses.
• Knowledge of how to improve code quality and optimize BI processes (e.g. speed, cost, reliability).
• Knowledge of modeling techniques.
• Experience gathering business requirements, using industry-standard business intelligence tool(s) to extract data, formulate metrics, and build reports.
Key job responsibilities
Gather requirements from stakeholders to build a suite of analytical and reporting solutions, utilizing the Amazon recruitment tools.
Query data using SQL for ad-hoc analyses, and publish high-quality dashboards and reports on tools like QuickSight, Tableau, or Microsoft Excel.
Provide timely execution of the full project lifecycle, including project planning, execution, risk assessment, and ensuring system availability.
Execute cross-functional, high-impact projects to improve operational performance and candidate experience.
Perform business analyses and query data using SQL, direct front-end system extracts, VBA macros, and other appropriate tools.
Clearly articulate the results of your analyses to support the overall decision-making process.
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