EU HVH Data Scientist / Funnel Management


At Amazon we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. Amazon is one of the most recognizable brand names in the world and we distribute millions of products each year to our loyal customers. We are seeking an outstanding Data Scientist to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems for our business lines in EU. You will design and run experiments, research new algorithms, and find new ways of optimizing the complex business strategy around high volume hiring (HVH) and data driven labor market analysis. Besides theoretical analysis and innovation, you will work closely with the HVH team to put algorithms into practice to monitor daily risk in workforce staffing across our different business lines. But you won’t stop there. Your role is also responsible for running location analysis and provide recommendations based on workforce staffing availability and costs to our senior leadership. Your work will directly impact our business and will drive building the right strategy for Customer Fulfillment in EU. The successful candidate for this role will be a data enthusiast, a fast learner and an innovative thinker. Additionally, is never satisfied with the status quo, can show success in following-up and getting things done and has the ability to thrive in a fast-paced, data-centric and ever-changing analytics environment. Main Responsibilities: - Develop real-time Labor Market Model - Monitor and identify risk across all customer fulfillment business lines in EU - Manage business and external stakeholders by using data driven risk assessments - Apply Statistical and Machine Learning methods to Labor market constraints and data - Design, develop and evaluate highly innovative models for predictive learning - Manage your own process: identify and execute on high impact projects, triage external requests, and make sure you bring projects to conclusion in time for the results to be useful - Communicate your results to diverse audiences with effective writing and visualizations BASIC QUALIFICATIONS • Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics or similar • Proven experience in Data-Modelling, Market-analysis, or related field • Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations • Able to drive clarity in the face of ambiguity PREFERRED QUALIFICATIONS • A strong track record of innovating through machine learning and statistical algorithms and their applications • Experience in planning and learning techniques mainly reinforcement learning and dynamic programming