About the job
The Director, Applied Science (Geospatial) owns the end-to-end science portfolio that enables these capabilities by leveraging innovative AI and ML techniques. They are responsible for (1) learning and improving a worldwide catalog of addresses with high-quality validation and geo-resolution, (2) building a places dataset to model where we delivery ranging from every single single-family home, campus, building, and apartment - along with their relationships and delivery critical attributes such as delivery hours, access information, mail rooms, delivery lockers, parking locations, entrances, and drop-off geocodes, (3) developing maps that capture a fresh and accurate road network, enable precise transit paths that optimize travel times while reducing travel risk in delivery routes and on-road navigation experiences and (4) developing feedback loops that leverage edge capabilities of millions of smart phones and tens of thousands of delivery vehicles to capture fresh street imagery, learn street signs, road markings, and road obstructions at scale, and reconstruct key delivery events and activities to improve the fidelity of address, place, and road datasets, optimize routes, and reduce defects.
Responsibilities
- Lead a worldwide team of scientists to develop and deploy AI and ML solutions for geospatial problems to accelerate and optimize Amazon's global delivery operations
- Interface with senior stakeholders across engineering, product, and operations teams to design end-to-end solutions, execute model delivery to production, and drive shared goals
- Contribute to strategic planning by developing yearly and 3-year planning documents
- Present to senior executives (VPs) and stakeholders via demo sessions, science reports, and quarterly business reports
- Drive innovation by leveraging SOTA scientific techniques ranging from GenAI (LLMs/VLMs/agents), computer vision, and traditional ML to solve delivery-related problems
- Build organizational capability by recruiting and promoting senior scientists and science leaders and maintain a high-performing team
Qualifications
Minimum
- MS in a quantitative field (CS, Math, Statistics, OR, Engineering etc.)
- 10+ years experience leading applied science and engineering teams in an industrial setting
- Proven experience of delivery of multiple science-based solutions to production with business impact
- Experience building and managing specialized teams of scientists (up to 50 people)
Preferred
- PhD in a quantitative field (CS, Math, Statistics, OR, Engineering etc.)
- Publications in top-tier AI and ML-focused conferences and journals
- Experience managing globally distributed teams
- Experience in delivery logistics