DESCRIPTION
Have you ever thought about what it takes to deliver high quality customer service at optimal cost? What would you do to take one of the best customer service organizations in the world to the next level? Do you enjoy working in an entrepreneurial, fast paced environment, solving complex problems and delivering innovative solutions? Do you like to innovate and simplify?
The Worldwide Capacity Planning (WWCP) organization owns the end-to-end workforce planning and execution of Amazon’s customer service network. Our forecasting, labor planning, scheduling, and real-time management solutions are responsible for the millions of daily decisions needed to provide efficient and frustration-free support to our customers around the world. We are looking for an experienced professional with excellent analytical skills and strong business acumen to join our Forecasting team.
As a Senior Forecast Analyst in WWCP, you will be responsible for modeling forecasting problems, discovering insights and identifying opportunities through the use of statistical, machine learning, algorithmic, data mining and visualization techniques. You will need to collaborate effectively with internal stakeholders and cross-functional teams to analyze forecast variances, understand and mitigate variance drivers, identify opportunities to improve operational efficiencies, and deliver successfully against high organizational standards. You should be able to apply a breadth of tools, data sources and analytical techniques to answer a wide range of high-impact business questions and present the insights in concise and effective manner. Additionally, you should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business. Accurate forecasts drive improvements in cost and quality of our customer service on a global scale.
This role requires a delicate balance in delivering models that are statistically grounded but also explainable operationally – business leaders must be able to understand what variables impact forecast variance and how they should respond tactically. This is a high visibility role with heavy interaction with senior leadership. Analytical ingenuity and leadership, coupled with demonstrated cross-functional partnership, are critical skills for this role.
The ideal candidate has an accomplished professional background with demonstrated proficiency in advanced mathematics and/or statistics. They are comfortable creating strategic recommendations in a thoughtful yet concise manner, and obtaining organizational “buy-in” at senior levels. They are well-organized, can manage multiple analyses/projects simultaneously, and are intellectually curious.
BASIC QUALIFICATIONS
– Bachelor’s degree in Business, Mathematics, Operations Research, Engineering or a related field
– 5+ years of experience as a business analyst or related positions
– Experience with statistical analysis and modeling
– Experience with SQL and one or more of the statistical modeling languages/ toolboxes (R, SAS, SPSS, Matlab, or Python)
– Excellent communication skills to share findings in an understandable and actionable manner
– Ability to work successfully in a dynamic, fast-paced environment
– Willing to work during the overlap as per US time zone.
PREFERRED QUALIFICATIONS
– MBA or Master’s degree in Mathematics, Statistics, Computer Science, Engineering or other business/analytical disciplines, with 7+ years of related work experience
– Experience in forecasting, time-series, and multivariate regression
– Combination of technical skills and business savvy to interface with all levels and disciplines across the organization
– Proven track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment Experience using AWS technologies such as Redshift, S3, etc.
– Excellent interpersonal, written and oral communication skills
– Natural curiosity and desire to learn