Business Analyst, Amazon Talent Acquisition

**This is a contract role for 1 year**

Are you passionate about driving business and customer impact through thoughtful analysis and data-driven insights? Are you a scientific thinker 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 Analyst 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 BA will bring innovation, a strategic perspective, a passionate voice, and an ability to prioritize and execute on a fast-moving set of priorities, competitive pressures, and operational initiatives. You will partner closely with program, product, and technology teams to define and build innovative and delightful experiences for customers. You must be highly analytical, able to work extremely effectively in a matrix organization, and have the ability to break complex problems down into steps that drive programs.

• Responsibilities:
• Converting data into digestible business intelligence and actionable information.
• Working with large data sets, automating data extraction, and building monitoring/reporting dashboards.
• Interacting with internal stakeholders to deep-dive into outlier events.
• Analyzing and solving business problems with a focus on understanding root causes and driving forward-looking opportunities.
• Communicating complex analysis and insights to our stakeholders and business leaders, both verbally and in writing.
• Enabling effective decision-making by retrieving and aggregating data from multiple sources and compiling it into a digestible and actionable format.
• Being open to learning and developing skillsets in the latest technologies and analytical techniques.
• Interacting with internal stakeholders to deep-dive outlier events.
  

Basic qualifications:

• BS in Computer Science, Degree in a quantitative discipline such as Statistics, Mathematics, Quantitative Finance, or Operations Research
• 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  Proficient in Microsoft Office, particularly Excel, with the ability to create dynamic reports and dashboards
• Analytical and problem-solving skills
• Experience with one or more industry analytics visualization tools (e.g. Tableau, QuickSight, MicroStrategy, PowerBI)
• Excellent English written and oral communication skills
  

Preferred Qualifications:

• Writing high quality SQL codes to retrieve and analyze data.
• Working with large data sets, automate data extraction, and build monitoring/reporting dashboard.

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

- 1+ years of tax, finance or a related analytical field experience
- 2+ years of complex Excel VBA macros writing experience
- Experience defining requirements and using data and metrics to draw business insights
- Experience with SQL or ETL

PREFERRED QUALIFICATIONS

- Experience working with Tableau
- Experience using very large datasets