About the job
Join Amazon's Global FP&A Technology (GFT) team as a Data Scientist, where you'll shape the future of FP&A operations by building the forecasting and AI capabilities behind Amazon's financial planning. As part of GFT's mission to streamline, optimize, and drive financial excellence through technology, you'll work closely with Corporate FP&A teams and cross-functional stakeholders to develop scalable data science solutions that support strategic finance objectives. Your work will contribute directly to enhancing reporting, planning, cost allocations, and business enablement tools that empower finance teams across the organization.
Responsibilities
1. Apply a range of data science methodologies — statistical modeling, machine learning, and time series analysis — to solve complex forecasting challenges.
2. Lead the end-to-end lifecycle of forecasting models — from research and experimentation through production launch — including defining success metrics, obtaining stakeholder sign-off, and managing rollout in collaboration with software and data engineering.
3. Run large-scale exploratory data analysis and rigorous experiments at scale to uncover patterns, evaluate models, and improve performance.
4. Partner with finance stakeholders, engineers, and other scientists to understand customer needs and deliver solutions that meet them.
5. Translate complex research findings into clear, factually correct documents and explain technical concepts to technical and non-technical audiences.
Qualifications
Minimum
- 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
- 2+ years of data scientist experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Currently has, or is in the process of obtaining, a Ph.D. in Math, Statistics, Computer Science, or related science field
- Experience applying theoretical models in an applied environment
Preferred
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company