WW Amazon Stores Finance Science (ASFS) works to leverage science and economics to drive improved financial results, foster data backed decisions, and embed science within Finance. ASFS is focused on developing products that empower controllership, improve business decisions and financial planning by understanding financial drivers, and innovate science capabilities for efficiency and scale. We are looking for a data scientist to lead high visibility initiatives for forecasting Amazon Stores' financials. You will develop new science-based forecasting methodologies and build scalable models to improve financial decision making and planning for senior leadership up to VP and SVP level. You will build new ML and statistical models from the ground up that aim to transform financial planning for Amazon Stores. We prize creative problem solvers with the ability to draw on an expansive methodological toolkit to transform financial decision-making with science. The ideal candidate combines data-science acumen with strong business judgment. You have versatile modeling skills and are comfortable owning and extracting insights from data. You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into business action. Key job responsibilities. Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models. Working with technical and non-technical stakeholders across every step of science project life cycle. Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models. Innovating by adapting new modeling techniques and procedures. Presenting research results to our internal research community. Basic Qualifications- 2 years of data scientist experience- 3 years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3 years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment- Bachelor's degree. Preferred Qualifications- Experience in a ML or data scientist role with a large technology company- Experience working on multi-team, cross-disciplinary projects- Experience effectively communicating complex concepts through written and verbal communication- Master's degree- Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems.