Job Highlight:
You will use data science methods to measure and model data related to environmental health and heat in urban areas. This will include contributing to the development of models for estimating high-resolution intra-urban temperature and heat indices and analyzing how heat influences human health and the resilience, social equity and economic performance of cities. You will sit in the Urban Data & Tools team in WRI Ross Center for Sustainable Cities and be affiliated with the WRI Data Lab. You will report to Senior Manager, Data & Tools, WRI Ross Center for Sustainable Cities.
What will you do:
Research and computational data analysis (60% time):
Apply knowledge of existing literature on urban climate modeling and environmental health to lead new tracks of work with the intent to contribute to the literature
Write performant code and use cloud computing to deliver novel and reproducible data insights and applications
Apply knowledge of Python and/or R to deliver reproducible analysis and data science applications
Apply knowledge of Weather Research and Forecasting (WRF) urban climate modeling, including key model features and datasets
Apply knowledge of packages for spatial analysis including GDAL and rasterio
Apply basic knowledge of frontend frameworks for data visualization. Contribute to research design and systems architecture decisions for data science analysis and applications
Bring a strong foundation of knowledge in general statistics and at least one area of specialization, e.g., spatial statistics, machine learning, epidemiology, or econometrics
Make novel statistical contributions to solving real world problems, selecting the right analysis approaches and algorithms
Be a statistical reviewer for both internal and external research
Apply understanding of research ethics to make ethical decisions in the real world
Mentor data analysts on computational tasks, providing code review and coaching them to learn new skills
Data management (20% time):
Organize and manage multiple data projects at one time using best practices for documentation
Apply knowledge of data across internal and external products to access a variety of structured data
Understand and fuse data from different sources (e.g., in-situ sensors for temperature and humidity, field surveys, and optical and radar remote sensors)
Apply knowledge of common database types to build automated data pipelines to pull and clean data without oversight
Apply knowledge for management of specialized datasets such as remote sensing data, including satellite imagery and radar, and field data collected via environmental sensors and ground surveys
Data communication (10% time):
Contribute significantly to the design of new data applications and products
Effectively communicate data to internal and external audiences using data visualization, clear writing, and compelling presentation skills
Lead the drafting of blogs, technical notes, and papers
Apply knowledge of cartographic principles and map design tools and practices
Project management (10% time):
Manage small teams of analysts, coordinators, and specialists to deliver projects with oversight from manager or Data Science Lead
Communicate work to non-technical, senior audiences internally and externally to ensure clarity and alignment
Understand and articulate where work fits within team and organization strategy
When called upon by manager or team lead, make meaningful contributions to fundraising and external partnership efforts such as through a draft technical capacity statement, research work plan, or a research budget
What will you need:
Education: You have a completed BA or BS degree in a relevant field, such as but not limited to geography, data science, urban studies, remote sensing or computer
Experience: You have 5+ years of full-time work experience related to public health, data science, urban studies, remote sensing, computer science, data product development, or other relevant topic
Past experience in the following is preferred: Developing high-resolution urban temperature and heat hazard models. Designing and launching new data analysis projects from concept to launch. Developing data processing pipelines for large and complex datasets. Deploying advanced statistics and methods to solve real-world problems
Working with data from a wide range of sources including in-situ sensors for temperature and humidity; field surveys; and optical and radar remote sensors
Write efficient and reproducible code using Python and/or R and git. Using cloud technologies including Google Cloud Platform and Amazon Web Services
Work in diverse environments and collaborating effectively with teams of diverse skill sets. Leading small teams to deliver data analysis and applications
Developing or directing development of data visualizations and map products
Languages: You have verbal and written proficiency in English required and additional fluency on a language spoken in WRI Offices preferred (e.g., Spanish, French, Portuguese, Chinese)
Requirements: Existing work authorization is required where this position is based. WRI is unable to authorize visa work authorization
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