Mohamed A M Elansary, PhD
Target: Staff Data Scientist, Weather — Waymo (Driving Quality & Scope Expansion)
Sourced insights (≤2)
- All-weather Driver: Waymo validates the Driver for rain, fog, sandstorms, and freezing temperatures with a systematic, scientific approach before advancing winter/snow capabilities — measurement first, then responsible scale with local-condition operating guidelines. Source: waymo.com/blog/2025/10/creating-an-all-weather-driver/
- JD Weather seat: Measure Waymo Driver performance in adverse/extreme weather (fog, rain, snow, ice, hail, flooding) and provide input on readiness to scale — plus 1P/2P/3P weather pipelines, spatio-temporal models, and measurement rigor for deployment/mitigation. Source: careers.withwaymo.com/jobs?gh_jid=8031401
Proof — hydrology UQ × adverse weather × multi-source data
- PhD Environmental Engineering, TAMUK 2022 (JD-preferred weather-adjacent field: Hydrology): multi-basin, multi-hydroclimate surface-water/groundwater forecast uncertainty quantification & reduction on HPC (MODFLOW, VIC, PIHM, NASA LIS; USGS/NOAA/NASA).
- Spatio-temporal adverse-weather signal: AMS 2021 floods & droughts (Brazos); multimodel streamflow forecasts across hydroclimates (AMS 2018); StormWater 1st Place poster (2017).
- Third-party weather/hydro data fluency + publication-grade QA — the same multi-source integration the Weather seat needs for weather intelligence pipelines.
- Ships production Python data/AI systems (Vertexium agentic LLM; EDAT Fortune 500 compliance) — measurement systems that reach stakeholders, not demos.
- Honest frame: weather-adjacent PhD + hydroclimate UQ — not AV fleet eval ownership; no invented pubs. Brand: the PhD who ships. Bay Area OK · Prefer take-home.