Data Scientist

Overview

Develop and deploy AI-driven metocean forecasting models in cloud environments.

Key Responsibilities

• cloud workflows
• model validation
• ml integration
• site forecasting
• ai weather
• cloud deployment

Tasks

-Manage cloud-based data workflows to ensure scalability and reliability. -Validate ML/AI models against observations to maintain scientific accuracy and performance. -Apply machine learning techniques to integrate metocean models and observations for site-specific forecasting. -Investigate, configure, and maintain AI-based weather models (such as Microsoft’s Aurora and Google DeepMind’s WeatherNext) in cloud environments like Azure or AWS.

Requirements

• machine learning
• phd
• statistical analysis
• cloud programming
• weather modeling
• computer science

What You Bring

-Proven experience and/or research in machine learning applications. -Master’s or PhD in Mathematics, Statistics, Computer Science, Physics, Meteorology, Oceanography, or a related discipline. -Background in statistical and mathematical analysis to support model development and validation. -Proudly Canadian – born and raised in Québec, now operating in over 40 countries. -Strong capability in computer science, ideally with cloud-based scientific programming experience. -Familiarity with AI-based weather modeling is an asset.

People Also Searched For

Benefits

-Limitless opportunities start here – tailor your role to match your ambition. -A global community of 72,000 brilliant minds – your next idea, mentor, or opportunity is always within reach. -Flexible work, real balance – because your growth drives ours.

About Wsp

-Partners with clients to create sustainable, efficient, and resilient solutions. -Known for iconic projects like the One World Trade Center and London's Crossrail. -Provides cutting-edge services in transportation, energy, water, and commercial developments. -Blends technical expertise with deep industry knowledge to solve complex challenges globally.

Sector Specialisms